Digital Document Analysis

Digital Document Analysis in Qualitative Research

online document analysis
digital text analysis
e-document analysis
digital archival analysis

2000s onward (grounded in earlier document analysis traditions)

Adapted from traditional document analysis; digital variant developed by qualitative researchers across disciplines (e.g., Bowen 2009; Prior 2003)

Digital document analysis is a qualitative method for systematically locating, appraising, and interpreting documents that exist in digital or online form — including websites, emails, institutional reports, policy files, social media content, and digital archives. It applies the established logic of document analysis to born-digital and digitised sources, enabling researchers to examine meaning, discourse, and institutional practice embedded in contemporary digital texts without recruiting participants.

Digital documents: websites, emails, social media posts, online reports, digital archives, PDFs, institutional digital records

Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40.

Prior, L. (2003). Using Documents in Social Research. Sage.

document-analysis content-analysis discourse-analysis digital-ethnography netnography visual-analysis


Digital Educational Action Research

technology-integrated action research
online educational action research
digital-mediated practitioner inquiry
DEAR

1990s–2000s (digital integration of Lewinian action research traditions)

Rooted in Carr & Kemmis (1986); digital adaptation developed by Lankshear, Knobel, and others from mid-1990s onward

Digital educational action research is a cyclical, practitioner-led inquiry method in which educators systematically investigate a problem or question arising in digitally mediated teaching and learning environments. Drawing on the action research tradition of Carr, Kemmis, and Lewin, it integrates digital tools — learning management systems, social media, video, online collaborative platforms — both as the context of inquiry and as instruments for data collection, making it particularly suited to contemporary technology-rich classrooms.

Applied qualitative-cyclical research design

Digital artifacts, online interactions, video recordings, screen captures, reflective journals, interview transcripts

Lankshear, C., & Knobel, M. (2004). A Handbook for Teacher Research: From Design to Implementation. Open University Press.

Carr, W., & Kemmis, S. (1986). Becoming Critical: Education, Knowledge and Action Research. Falmer Press.

educational-action-research participatory-action-research design-based-research digital-classroom-observation lesson-study program-evaluation


Digital Ethnography

online ethnography
virtual ethnography
internet ethnography
netnography

Christine Hine (virtual ethnography); Robert V. Kozinets (netnography)

Digital ethnography is a qualitative research method that adapts traditional ethnographic fieldwork to online and digitally mediated settings. Drawing on sustained participant observation, document collection, and sometimes interviews, the researcher immerses themselves in one or more digital communities — social media platforms, forums, gaming spaces, or messaging groups — to understand how culture, identity, and social practice are constructed through digital interaction. The approach recognises that online spaces are not merely reflections of offline life but distinctive sites of cultural production in their own right.

Online text, multimedia, social media posts, forum discussions, field notes, interviews conducted digitally

1–3 online communities or platforms; dozens to hundreds of textual artefacts

Kozinets, R. V. (2010). Netnography: Doing Ethnographic Research Online. Sage.

Hine, C. (2000). Virtual Ethnography. Sage.

ethnography discourse-analysis content-analysis thematic-analysis grounded-theory narrative-analysis


Digital Grounded Theory

DGT
online grounded theory
internet-based grounded theory
grounded theory in digital contexts

2000s–2010s (as digital data became mainstream in qualitative research)

Adapted from Glaser & Strauss (1967); digital application developed through the work of Murthy (2008) and others in online qualitative research

Digital Grounded Theory applies the systematic inductive logic of grounded theory to data gathered from digital and online environments — social media platforms, forums, blogs, comment sections, and other internet-mediated communication. Rather than simply using grounded theory on text that happens to come from digital sources, it involves adapting sampling, collection, and ethical procedures to the specific affordances and constraints of online data, while retaining the core commitment to theory generation grounded in empirical material.

Digital text data: social media posts, online forums, blogs, emails, digital documents, chat logs

Murthy, D. (2008). Digital ethnography: An examination of the use of new technologies for social research. Sociology, 42(5), 837–855.

Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine.

grounded-theory digital-ethnography netnography constructivist-grounded-theory digital-thematic-analysis digital-content-analysis


Digital Health Acceptance Scale

Fred D. Davis (Technology Acceptance Model); extended by Venkatesh et al. (Unified Theory of Acceptance and Use of Technology)

The Digital Health Acceptance Scale measures the extent to which patients and providers perceive digital health technologies as useful, easy to use, and worth adopting. Grounded in Davis's Technology Acceptance Model (TAM) and extended by Venkatesh and colleagues through the Unified Theory of Acceptance and Use of Technology (UTAUT), the scale captures both intrinsic factors (usefulness, ease of use, subjective norms) and contextual factors (facilitating conditions, effort expectancy) that predict technology adoption and sustained use in healthcare settings.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.


Digital Hermeneutic Analysis

digital hermeneutics
computational hermeneutics
digital text interpretation
DHA

Extends classical hermeneutics (Schleiermacher, Dilthey, Gadamer, Ricoeur) into digital contexts; Roberto Simanowski and others in digital humanities

Digital hermeneutic analysis applies the classical tradition of hermeneutic interpretation — rooted in Schleiermacher, Dilthey, Gadamer, and Ricoeur — to born-digital and digitised texts, online corpora, and digital artifacts. It asks not only what digital objects mean, but how digital mediation, platform architecture, and computational affordances shape the conditions of meaning itself. The method is prominent in digital humanities, digital history, and media studies.

Qualitative interpretive research design

Digital texts, born-digital documents, digital artifacts, online corpora

Simanowski, R. (2010). Digital Hermeneutics: Interpreting (with) the Machine. Journal of Visual Culture, 9(1), 84–106.

hermeneutic-analysis textual-criticism digital-historical-archival-research digital-textual-criticism discourse-analysis content-analysis


Digital Hermeneutic Phenomenology

Digital Hermeneutic Phenomenological Research

online hermeneutic phenomenology
digital HP
web-based hermeneutic phenomenology
virtual hermeneutic phenomenology

2000s–2010s (digital adaptation of van Manen's 1990 framework)

Grounded in Max van Manen's hermeneutic phenomenology; digital adaptation developed by qualitative researchers from the 2000s onward

Digital Hermeneutic Phenomenology applies van Manen's hermeneutic phenomenological tradition to phenomena that are lived, shaped, or mediated through digital technologies and online environments. Rather than treating the digital channel as a mere convenience for data collection, this approach treats participants' online experiences as phenomena worthy of interpretive inquiry in their own right — asking what it means to live, relate, learn, or work in and through digital spaces.

Online interviews (video, chat, email), digital narratives, online diaries, social media posts, digital artefacts

van Manen, M. (1990). Researching Lived Experience: Human Science for an Action Sensitive Pedagogy. State University of New York Press.

Salmons, J. (2014). Qualitative Online Interviews: Strategies, Design, and Skills (2nd ed.). SAGE Publications.


Digital Historical Archival Research

digital archival research
digital archive history
online archival research
digital humanities archival method

1990s–2000s (as digital archives became widely accessible)

Emerging practice across digital humanities scholars; Roy Rosenzweig among early proponents

Digital historical archival research is the systematic investigation of the past using digitized primary sources held in online repositories, digital archives, and electronic databases. It combines the interpretive principles of traditional historical archival research with digital tools for search, retrieval, text mining, and visualization, enabling researchers to access geographically dispersed collections, apply computational analysis to large corpora, and reconstruct historical events, processes, and social phenomena from preserved primary evidence.

Digitized primary sources, scanned documents, online databases, digital repositories

Theimer, K. (2012). What is the Meaning of Archives 2.0? American Archivist, 75(1), 58–68.


Digital Institutional Ethnography

Digital IE
online institutional ethnography
virtual institutional ethnography
digital Smith IE

IE: 1980s–1990s; digital adaptation: 2000s–2010s

Dorothy E. Smith (IE foundations); extended by IE scholars to digital contexts

Digital Institutional Ethnography (Digital IE) applies Dorothy E. Smith's institutional ethnography framework to digital and online settings. It investigates how institutional ruling relations — the texts, policies, and coordination mechanisms that organize people's everyday lives — operate through digital infrastructures such as platforms, software systems, online documents, and algorithmic processes. The goal is to make visible how digital tools and texts coordinate and subordinate experience to institutional interests.

Digital texts, online documents, digital interaction logs, interviews, screen recordings

Smith, D. E. (2005). Institutional Ethnography: A Sociology for People. AltaMira Press.

Grahame, P. R., & Grahame, M. (2020). Institutional Ethnography and the Digital Turn: Researching Online Coordination of Work. Qualitative Sociology Review, 16(1), 6–24.

institutional-ethnography digital-ethnography netnography critical-discourse-analysis document-analysis participatory-digital-ethnography


Digital Interpretive phenomenological analysis

internet-based interpretive phenomenological analysis

IPA founded ~1996; digital variant established practice ~2010–2020

Jonathan A. Smith (IPA); adapted to digital contexts by qualitative internet researchers from ~2010s onward

Digital Interpretive Phenomenological Analysis (Digital IPA) applies the rigorous IPA framework — originally developed by Jonathan Smith to explore how individuals make sense of significant lived experiences — within digital data-collection environments. Participants are recruited and interviewed online (via video call, synchronous text chat, email, or digital diary), and the resulting transcripts and digital texts are analysed through the same close-reading, emergent-coding, and cross-case patterning procedures that define standard IPA. The digital setting both expands access to geographically dispersed or hard-to-reach participants and introduces distinct methodological considerations around rapport, embodied cues, and data authenticity.

Qualitative research design and analytic approach

Online interviews (video, text, asynchronous), digital diaries, online focus groups, social media narratives

Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretative Phenomenological Analysis: Theory, Method and Research. Sage.

Salmons, J. (2015). Qualitative Online Interviews: Strategies, Design and Skills (2nd ed.). Sage.

interpretive-phenomenology digital-ethnography digital-narrative-research digital-hermeneutic-phenomenology online-qualitative-research netnography


Digital Life History Research

digital life story research
DLHR
online life history method
digital biographical method

2000s (digital turn in life history; rooted in life history tradition since ~1920s)

Building on Goodson, Roberts, and broader biographical research traditions; digital extension from 2000s onward

Digital Life History Research is a qualitative biographical method that investigates how individuals construct, narrate, and preserve their life stories using digital tools and environments. It extends the classical life history tradition into online spaces — gathering data through video interviews, asynchronous email narratives, digital diaries, social media timelines, and multimedia life documents — to understand personal and social experience across time.

Qualitative biographical research design

Digital narratives, online interviews, social media content, multimedia life documents

Goodson, I., & Gill, S. (2017). The Narrative Turn in Social Research. In I. Goodson & M. Andrews (Eds.), Considering Counter-Narratives (pp. 1–24). John Benjamins.

Roberts, B. (2002). Biographical Research. Open University Press.

life-history-research narrative-inquiry autoethnography oral-history digital-ethnography biographical-method


Digital Metaphor analysis

online metaphor analysis
digital metaphor research
metaphor analysis of digital texts
DMA

Rooted in Lakoff & Johnson (1980); extended to digital contexts by corpus and computational linguists from the 2000s onward

Digital Metaphor Analysis (DMA) is a qualitative research approach that identifies, maps, and interprets conceptual metaphors embedded in digital texts — social media posts, online forums, blogs, comment sections, and other internet-mediated communication. Drawing on Conceptual Metaphor Theory (Lakoff and Johnson 1980), it examines how users frame abstract ideas (identity, politics, health, crisis) through systematic metaphorical mappings, revealing shared conceptual structures and ideological orientations within online discourse communities.

Digital texts: social media posts, online forums, blogs, chat logs, news comments

Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. University of Chicago Press.

Charteris-Black, J. (2004). Corpus Approaches to Critical Metaphor Analysis. Palgrave Macmillan.

metaphor-analysis critical-metaphor-analysis digital-discourse-analysis digital-content-analysis digital-thematic-analysis semiotic-analysis


Digital Multiple case study

online multiple case study
digital multi-site case study
virtual multiple case study
digital comparative case inquiry

1984 (Yin's case study framework); digital adaptation ~2000s–2010s

Robert K. Yin (case study methodology); extended to digital contexts by various digital methods scholars

Digital Multiple Case Study is a qualitative research design in which two or more bounded digital cases — such as online communities, social media platforms, virtual organizations, or digital ecosystems — are studied in depth and then compared systematically. Grounded in Yin's case study methodology and adapted for digital settings, the approach combines the contextual richness of single-case inquiry with the analytic leverage of cross-case comparison in online environments.

Digital documents, online interactions, digital artifacts, virtual interviews, screen recordings, social media data

Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage.

Kozinets, R. V. (2020). Netnography: The Essential Guide to Qualitative Social Media Research (3rd ed.). Sage.

multiple-case-study digital-ethnography comparative-case-study netnography digital-narrative-research digital-thematic-analysis


Digital Narrative Research

digital storytelling research
DNR
digital narrative inquiry
digital story-based research

Mid-1990s (practice); 2000s (formalised as research methodology)

Joe Lambert & Dana Atchley (Center for Digital Storytelling, Berkeley); theorised in research contexts by John Hartley, Kathy McWilliam, and Michele Knobel

Digital Narrative Research is a qualitative methodology in which participants create or share short digital stories — typically combining personal voice-over, photographs, video, and text — that become the primary data for inquiry. Originating in community digital-storytelling practice developed at the Center for Digital Storytelling in Berkeley in the 1990s, the approach has been adopted widely in education, health, social work, and participatory action research to surface voices and experiences that are difficult to capture through interviews or surveys alone.

Digital artefacts: short video stories, audio recordings, blogs, social media posts, photographs, multimodal documents

Lambert, J. (2013). Digital Storytelling: Capturing Lives, Creating Community (4th ed.). Routledge.

Hartley, J., & McWilliam, K. (Eds.). (2009). Story Circle: Digital Storytelling Around the World. Wiley-Blackwell.

narrative-inquiry digital-ethnography multimodal-analysis photo-voice thematic-analysis discourse-analysis


Digital Oral History Method

digital oral history
DOH
digital life history interview
digital recorded oral testimony

2000s (digital variant of oral history established 1940s–1950s)

Oral History Association; Donald Ritchie; Alessandro Portelli (digital turn elaborated early 2000s)

The digital oral history method is a qualitative research approach in which personal testimonies and lived experiences are elicited through recorded interviews, then preserved, managed, and disseminated using digital technologies. Building on the established oral history tradition, the digital variant leverages audio and video recording equipment, digital archiving platforms, and online dissemination channels to expand access, ensure long-term preservation, and enable richer multi-modal analysis of narrator accounts.

Digital audio/video recordings, transcripts, metadata-tagged archives

Ritchie, D. A. (2003). Doing Oral History: A Practical Guide (2nd ed.). Oxford University Press.

Alexander, B., Boyd, D., & House, M. (2007). Oral history and digital humanities: Voice, access, and engagement. Oral History Review, 34(2), 1–15.

oral-history-method ethnography narrative-analysis life-history-research digital-ethnography archival-research


Digital Oral History

digital oral history
DOH
digital oral narrative research
online oral history

1990s–2000s (systematic digital integration)

Oral history tradition (Allan Nevins, 1940s); digital adaptation by Michael Frisch and others from the 1990s onward

Digital Oral History is a qualitative research method that uses digital technologies — audio and video recorders, online platforms, and digital archives — to collect, preserve, and disseminate first-person oral accounts of lived experience. It extends the established oral history tradition by leveraging digital tools to enhance accessibility, reach geographically dispersed participants, and enable long-term preservation and public engagement with recorded narratives.

Qualitative research design with digital data collection and archiving

Audio and video recordings, digital transcripts, online narrative accounts

Boyd, D., & Larson, M. (Eds.). (2014). Oral History and Digital Humanities: Voice, Access, and Engagement. Palgrave Macmillan.

Frisch, M. (2006). Oral History and the Digital Revolution: Toward a Post-Documentary Sensibility. In R. Perks & A. Thomson (Eds.), The Oral History Reader (2nd ed., pp. 102–114). Routledge.

oral-history digital-narrative-research digital-ethnography digital-life-history-research narrative-inquiry digital-biographical-research


Digital Phenomenology

online phenomenology
virtual phenomenology
phenomenology of digital experience
digitally-mediated phenomenology

Emerging from classical phenomenology (Husserl, Heidegger) applied to digital contexts; synthesised by scholars such as Sarah Pink and Mark D. Vagle

Digital Phenomenology is a qualitative research approach that applies phenomenological inquiry to lived experiences mediated by or situated within digital environments — including social media platforms, virtual communities, online spaces, and interactions with digital technologies. It asks how people experience, make meaning of, and embody their encounters with digital tools and online worlds, using the interpretive and descriptive rigour of classical phenomenology in settings where much or all of the experience unfolds online.

Online interviews, digital artifacts, social media posts, screen recordings, digital diaries, virtual observation notes

Pink, S., Horst, H., Postill, J., Hjorth, L., Lewis, T., & Tacchi, J. (2016). Digital Ethnography: Principles and Practice. Sage.

Vagle, M. D. (2018). Crafting Phenomenological Research (2nd ed.). Routledge.

phenomenology interpretive-phenomenology digital-ethnography netnography digital-narrative-research hermeneutic-phenomenology


Digital Program Evaluation

technology-enhanced evaluation
digital evaluation
e-evaluation
online program evaluation

2000s–2010s (formalized alongside proliferation of digital programs and online data)

Evolving practice; rooted in Rossi, Lipsey & Freeman's evaluation tradition; extended by digital methods scholars in the 2000s–2010s

Digital program evaluation applies the systematic logic of program evaluation to programs that operate fully or partly in digital environments, using digital tools and data — web analytics, online surveys, platform logs, social media metrics, and digital trace data — to assess program reach, implementation fidelity, and outcomes. It retains the core evaluative commitment to rendering a defensible judgment about program merit and worth while exploiting the speed, scale, and granularity that digital data sources offer. Applications span online education, digital public health campaigns, e-government services, and technology-mediated social programs.

Digital trace data, web analytics, online surveys, administrative records, social media data, digital platform logs

George, S., & Leidner, D. (2020). Digital Evaluation: Leveraging Digital Data and Methods for Program Assessment. Routledge.

Russ-Eft, D., & Preskill, H. (2009). Evaluation in Organizations: A Systematic Approach to Enhancing Learning, Performance, and Change (2nd ed.). Basic Books.

program-evaluation digital-content-analysis digital-case-study educational-action-research curriculum-analysis mixed-methods-research


Digital Qualitative Content Analysis

qualitative content analysis of digital data

2010s (building on qualitative content analysis traditions from 1983–2012)

Adapted from Philipp Mayring and Margrit Schreier; digital extension by multiple scholars in the 2010s

Digital Qualitative Content Analysis (DQCA) is a systematic method for interpreting meaning from digital texts — social media posts, forum threads, blogs, emails, and other online content — through a structured, category-driven coding process. It extends the established tradition of qualitative content analysis (Mayring; Schreier) to the scale, multimodality, and contextual specificity of digital environments, prioritising interpretive depth over frequency counting.

Digital texts: social media posts, online forums, websites, chat logs, emails, blog content

Schreier, M. (2012). Qualitative Content Analysis in Practice. Sage.

Stoltenberg, I., & Mruck, K. (2023). Qualitative content analysis in the digital age: Challenges and opportunities. Forum: Qualitative Social Research, 24(1).

qualitative-content-analysis thematic-analysis discourse-analysis netnography social-media-analysis grounded-theory


Digital Reflexive Thematic Analysis

digital RTA
online reflexive thematic analysis
RTA for digital data

2006 (RTA foundation); digital application consolidated ~2019–2022

Virginia Braun & Victoria Clarke (reflexive foundation); extended by digital qualitative researchers

Digital Reflexive Thematic Analysis (Digital RTA) applies Braun and Clarke's reflexive thematic analysis framework to qualitative data generated in or collected from digital environments — including social media posts, online forums, chat transcripts, email, digital interviews, and other online texts. It foregrounds the researcher's active, interpretive role and treats theme generation as a creative-analytic act shaped by the analyst's theoretical positioning rather than a mechanical coding procedure.

Digital text, social media posts, online interviews, forum threads, chat logs

Braun, V., & Clarke, V. (2022). Thematic Analysis: A Practical Guide. Sage.

Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597.

reflexive-thematic-analysis thematic-analysis digital-ethnography netnography content-analysis framework-analysis


Digital Semiotic Analysis

DSA
digital semiotics
online semiotic analysis
digital sign analysis

Classical semiotics early 20th century; digital adaptation from the 1990s onward

Rooted in Ferdinand de Saussure and Charles S. Peirce; digital applications developed by scholars such as David Chandler and Gunther Kress

Digital Semiotic Analysis applies the classical study of signs and meaning-making to content produced and circulated in digital environments. It examines how signifiers — words, images, icons, sounds, emojis, hyperlinks, and interface conventions — create meaning within digital texts such as websites, social media posts, memes, and online advertisements. The method draws on Saussurean dyadic semiotics and Peircean triadic semiotics, extended by Roland Barthes's connotation and myth framework and by contemporary multimodal semiotic theory developed for screen-based media.

Digital texts, images, videos, memes, websites, social media posts, emojis, hyperlinks

Chandler, D. (2007). Semiotics: The Basics (2nd ed.). Routledge.

Jewitt, C. (Ed.). (2009). The Routledge Handbook of Multimodal Analysis. Routledge.

semiotic-analysis visual-analysis discourse-analysis critical-discourse-analysis content-analysis multimodal-analysis


Digital Signature Scheme

Digital Signature and Authentication Framework

Digital Signature Algorithm
Message Authentication and Integrity
Public Key Signature

Ronald Rivest, Adi Shamir, Leonard Adleman

A digital signature scheme provides authentication, integrity assurance, and non-repudiation of electronically signed documents. Using public-key cryptography (such as RSA, DSA, or ECDSA), the originator signs a message with a private key in a way that any recipient can verify the signature using the originator's public key, proving that the message was created by the claimed author and has not been tampered with.

Rivest, R. L., Shamir, A., & Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, 21(2), 120–126.

Krawczyk, H., Bellare, M., & Herbst, R. (1997). HMAC: Keyed-hashing for message authentication. RFC 2104.

Johnson, D., Menezes, A., & Vanstone, S. (2001). The elliptic curve digital signature algorithm (ECDSA). International Journal of Information Security, 1(1), 36–63.

rsa-cryptosystem-analysis sha-hash-function tls-protocol-analysis diffie-hellman-key-exchange


Digital Soil Mapping

DSM
predictive soil mapping
quantitative soil-landscape modelling
geostatistical soil mapping

Late 1990s – early 2000s (formalised ~2003)

Multiple contributors; foundational framework by Alex McBratney and colleagues

Digital Soil Mapping (DSM) is a quantitative, data-driven pipeline that predicts the spatial distribution of soil properties and classes across a landscape by statistically linking field observations to environmental covariates — terrain attributes, remote sensing imagery, climate surfaces, and geology layers. The approach replaces or augments traditional expert-drawn soil surveys with reproducible, spatially explicit models, and is applied in agronomy, land management, food security, and environmental assessment.

Soil sample observations, terrain derivatives, remote sensing imagery, climate layers (raster and point data)

McBratney, A. B., Mendonca Santos, M. L., & Minasny, B. (2003). On digital soil mapping. Geoderma, 117(1–2), 3–52.

Minasny, B., & McBratney, A. B. (2016). Digital soil mapping: A brief history and some lessons. Geoderma, 264, 301–311.

geostatistics remote-sensing random-forest kriging land-use-change-analysis precision-agriculture


Digital Straussian Grounded Theory

digital GT (Straussian)
Straussian GT in digital contexts
online Straussian grounded theory
digital Strauss-Corbin grounded theory

1990 (Strauss & Corbin foundational); digital adaptation 2000s–2010s

Anselm Strauss & Juliet Corbin (foundational GT); adapted to digital contexts by subsequent methodologists

Digital Straussian grounded theory applies the systematic, coding-driven approach of Strauss and Corbin's grounded theory to digital data sources such as online forums, social media, chat logs, and digital documents. It retains the Straussian paradigm model and three-stage coding structure — open, axial, and selective — while adapting sampling strategies, theoretical saturation criteria, and ethical protocols to the unique features of online and digital research environments.

Qualitative research design and analysis approach

Digital text data: online forums, social media posts, chat logs, emails, digital documents

Strauss, A., & Corbin, J. (1998). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory (2nd ed.). Sage.

Charmaz, K. (2014). Constructing Grounded Theory (2nd ed.). Sage. [Includes comparative methodological context on Straussian vs. constructivist GT and digital data adaptation]

grounded-theory constructivist-grounded-theory classic-grounded-theory thematic-analysis netnography digital-ethnography


Digital Textual Criticism

digital philology
computational textual criticism
digital scholarly editing
digital critical editing

1990s–2000s (mature field by early 2000s)

Patrick Sahle, Peter Robinson, and the digital humanities community (building on traditional textual criticism)

Digital textual criticism is the application of computational and digital methods to the scholarly analysis, collation, and editing of historical texts. Building on centuries-old philological practice, it uses tools such as XML/TEI encoding, automated collation software (e.g., CollateX), and computational stemmatology to compare manuscript witnesses, reconstruct textual transmission histories, and produce digital critical editions that are richer and more transparent than their print counterparts.

Manuscript images, transcriptions, XML/TEI-encoded texts, variant readings

Sahle, P. (2013). Digitale Editionsformen. Zum Umgang mit der Überlieferung unter den Bedingungen des Medienwandels. 3 vols. Norderstedt: Books on Demand.

Robinson, P. (2013). Towards a theory of digital editions. Variants: The Journal of the European Society for Textual Scholarship, 10, 105–131.

textual-criticism hermeneutic-analysis historical-archival-research document-based-textual-criticism digital-hermeneutic-analysis comparative-textual-criticism


Digital Thematic Analysis

online thematic analysis
social media thematic analysis
digital TA
web-based thematic analysis

2006 (base method); digital application 2010s

Virginia Braun & Victoria Clarke (base method); extended to digital data contexts by qualitative digital researchers from the mid-2000s onward

Digital Thematic Analysis applies Braun and Clarke's six-phase thematic analysis framework to qualitative data generated in or harvested from digital environments — including social media platforms, online forums, blogs, digital interview transcripts, and user-generated web content. It retains the same systematic coding logic as standard thematic analysis while incorporating additional decisions about data demarcation, platform context, and the ethical handling of publicly available digital material.

Social media posts, online forum threads, blog content, digital interview transcripts, online news comment sections, user-generated digital texts

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.

Rich, J. L., & Creighton, K. (2021). Using thematic analysis in digital social research: Methodological considerations for analysing social media data. International Journal of Social Research Methodology, 24(5), 571–583.

thematic-analysis reflexive-thematic-analysis digital-content-analysis digital-discourse-analysis digital-ethnography comparative-thematic-analysis


Digital Transformation Readiness Scale

Digital Transformation Readiness and Maturity Assessment Scale

Digital Readiness Scale
Digital Maturity Scale
Digital Transformation Assessment

George Westerman, Didier Bonnet, Andrew McAfee (MIT Center for Digital Business)

Digital Transformation Readiness refers to an organization's preparedness to successfully adopt digital technologies, redesign business processes, and develop new digital capabilities to compete in increasingly digital markets. Westerman, Bonnet, and McAfee (2014) identify nine elements of digital transformation spanning technology (systems, data, infrastructure), people (skills, culture), and governance (leadership, decision authority). Organizations with high digital readiness leverage digital technologies to create competitive advantage; those with low readiness experience failed technology implementations, continued legacy system dependence, and competitive disadvantage. This scale measures organizational readiness across four dimensions: technology capability, people and skills, organizational culture, and governance and leadership—revealing where transformation barriers exist.

Westerman, G., Bonnet, D., & McAfee, A. (2014). The nine elements of digital transformation. MIT Sloan Management Review, 55(3), 1–6.

Fitzgerald, M., Kruschwitz, N., Bonnet, D., & Welch, M. (2014). Embracing digital technology: A new strategic imperative. MIT Sloan Management Review Research Report.

Nadkarni, S., & Prügl, R. (2021). Digital transformation: A review, synthesis and opportunities for future research. Management Review Quarterly, 71(2), 233–341.

dynamic-capabilities-scale knowledge-management-scale organizational-resilience-scale strategic-orientation-scale supply-chain-integration-scale


Digital Twin Simulation

Digital Twin Simulation (Hybrid Physics-ML Virtual Replica)

Dijital İkiz Simülasyonu (Digital Twin)
digital twin
digital shadow
cyber-physical twin

2002 (concept); 2014 (white paper formalization)

Michael Grieves (University of Michigan, 2002; white paper 2014)

Digital Twin Simulation, first conceptualised by Michael Grieves at the University of Michigan around 2002 and formally described in his 2014 white paper, creates a continuously updated virtual copy of a physical system by fusing real-time sensor data with a mechanistic (physics-based) model and machine-learning components. The twin mirrors the physical asset's current state and projects its future behaviour, enabling fault detection, predictive maintenance, and operational optimisation without disrupting the real system.

Hybrid physics-based + machine-learning simulation

Real-time or high-frequency IoT sensor stream

Continuous state estimation loop (e.g., Kalman filter or ML surrogate)

Output: Predicted system state, fault probability, maintenance schedule

Manufacturing, engineering, healthcare, smart infrastructure, aerospace

Grieves, M. (2014). Digital Twin: Manufacturing Excellence through Virtual Factory Replication. White Paper, University of Michigan.

Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H. & Sui, F. (2018). Digital Twin-Driven Product Design, Manufacturing and Service with Big Data. The International Journal of Advanced Manufacturing Technology, 94, 3563-3576.

agent-based-simulation monte-carlo-simulation kalman-filter state-space-model iot-time-series system-dynamics


Digital Visual Analysis

DVA
digital image analysis
online visual analysis
digital visual research

Gillian Rose; Sarah Pink (digital extension)

Digital visual analysis is a qualitative approach for systematically examining visual materials that originate in, circulate through, or are consumed within digital environments — including social media images, video content, screenshots, memes, infographics, and online multimodal texts. Drawing on visual methodologies and digital research methods, it attends not only to what images depict but also to how they are produced, shared, and interpreted within specific digital platforms and social contexts.

Digital images, video, social media visuals, screenshots, memes, online multimodal content

Rose, G. (2016). Visual Methodologies: An Introduction to Researching with Visual Materials (4th ed.). Sage.

Pink, S. (2021). Doing Visual Ethnography (4th ed.). Sage.

visual-analysis digital-ethnography netnography content-analysis semiotic-analysis discourse-analysis


Digital Wellbeing Scale

Isabel Pinto de Azevedo, Bárbara Marques, and José Mata

The Digital Wellbeing Scale is a multidimensional self-report instrument that assesses positive and negative aspects of technology use, capturing not just problematic behaviors but also digital resources supporting wellbeing. Developed by Azevedo and colleagues in 2022, this scale recognizes that digital engagement exists on a spectrum from harmful to beneficial, and measures protective factors alongside risk factors.

Azevedo, I. P., Marques, B., & Mata, J. (2022). Development and psychometric evaluation of a digital wellbeing scale. Telematics and Informatics, 67, 101765.

social-media-disorder-scale smartphone-addiction-scale-short technoference-scale fear-of-missing-out-scale


Dijkstra Algorithm

Dijkstra's algorithm
shortest path algorithm

Dijkstra's Algorithm, introduced by Edsger W. Dijkstra in 1956, is one of the most fundamental algorithms in computer science for solving the single-source shortest path problem. It finds the shortest path from a starting vertex to all other vertices in a weighted graph with non-negative edge weights.

Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269-271.

Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to Algorithms (3rd ed.). MIT Press.


Dilated CNN

Dilated Convolutional Network (WaveNet / Temporal Convolutional Network)

Dilate Edilmiş CNN (WaveNet / TCN)
WaveNet
Temporal Convolutional Network
TCN
dilated convolution

van den Oord, A. et al.; Bai, S., Kolter, J.Z. & Koltun, V.

A Dilated CNN is a one-dimensional convolutional network whose receptive field grows exponentially with depth, letting it model long-range structure in time series and audio signals. WaveNet (van den Oord et al., 2016) and the Temporal Convolutional Network of Bai, Kolter and Koltun (2018) are the prominent members of this family.

Deep learning (dilated 1D convolutional network)

Time-series forecasting & sequence prediction

van den Oord, A. et al. (2016). WaveNet: A Generative Model for Raw Audio. arXiv.

Bai, S., Kolter, J.Z. & Koltun, V. (2018). An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. arXiv:1803.01271.

gru bidirectional-rnn seq2seq random-forest xgboost


DINA Model

Deterministic Inputs, Noisy Outputs Model

The DINA Model (Deterministic Inputs, Noisy Outputs) is a cognitive diagnostic model developed by Junker and Sijtsma (2001) that classifies examinees into latent skill classes based on their item response patterns. DINA assumes a deterministic relationship between skill mastery and correct responses, with probabilistic error accounting for guessing and slips.

Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25(3), 258-272.

Haertel, E. H. (1989). Using restricted latent class models to map the skill structure of achievement items. Journal of Educational Measurement, 26(4), 301-321.

de la Torre, J. (2009). DINA model and parameter estimation: A didactic perspective. Journal of Educational and Behavioral Statistics, 34(1), 115-130.

dino-model rule-space-methodology cognitive-diagnostic-cat necessary-condition-analysis


DINO Model

Deterministic Inputs, Noisy Outputs Model (Disjunctive)

The DINO Model (Deterministic Inputs, Noisy Outputs—Disjunctive) is a cognitive diagnostic model that relaxes DINA's conjunctive (AND) skill requirement logic. DINO assumes an examinee only needs to master one of multiple possible skill pathways to answer an item correctly, making it suitable for scenarios where skills are substitutable or alternative routes to success exist.

Templin, J., & Henson, R. A. (2006). Measurement of psychological disorders using cognitive diagnosis models. Psychological Methods, 11(3), 287-305.

de la Torre, J. (2019). Cognitive Diagnosis Models for Polytomous Data. In B. Bolt & M. Robitzsch (Eds.), Innovative Assessment: Technologies and Methodologies (pp. 110-128). Oxford University Press.

dina-model rule-space-methodology cognitive-diagnostic-cat necessary-condition-analysis


Direct Numerical Simulation

Direct Numerical Simulation (DNS) is a computational approach that solves the Navier-Stokes equations without turbulence models, resolving all scales of motion from the largest energy-containing eddies down to the smallest dissipative scales (Kolmogorov microscales). Pioneered by Steven Orszag in 1971, DNS provides complete information about turbulent flow fields and serves as a reference solution for validating turbulence models. However, extreme computational demands limit DNS to relatively simple geometries and low to moderate Reynolds numbers.

Orszag, S. A. (1971). Numerical simulation of incompressible flows within simple boundaries: accuracy. Journal of Fluid Mechanics, 49(1), 75-112.

Moin, P., & Mahesh, K. (1998). Direct numerical simulation: a tool in turbulence research. Annual Review of Fluid Mechanics, 30, 539-578.

Kim, J., Moin, P., & Moser, R. (1987). Turbulence statistics in fully developed channel flow at low Reynolds number. Journal of Fluid Mechanics, 177, 133-166.

large-eddy-simulation reynolds-averaged-navier-stokes lattice-boltzmann-method smoothed-particle-hydrodynamics boundary-layer-theory


Direct Preference Optimization

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Deep Learning, Language Models, RLHF Alternatives

Direct Preference Optimization (DPO) is a training method introduced by Rafailov et al. in 2023 that aligns language models with human preferences without requiring an explicit reward model. By directly optimizing for preference pairs (better response vs worse response), DPO simplifies the training pipeline compared to reinforcement learning from human feedback (RLHF).

Rafailov, R., Sharma, A., Mitchell, E., Manning, C. D., Ermon, S., & Finn, C. (2023). Direct preference optimization: Your language model is secretly a reward model. arXiv preprint arXiv:2305.18290.

qlora mamba latent-diffusion-models masked-autoencoders


Direct Torque Control

Direct Torque Control (DTC) is a method for controlling induction motors by directly manipulating magnetic flux and torque through switching of power converter inverter arms. Introduced by Takahashi and Noguchi in 1986, DTC provides fast torque response, low harmonic distortion, and robust performance without requiring current controllers or coordinate transformations, making it ideal for high-performance drive applications.

Takahashi, I., & Noguchi, T. (1986). A new quick-response and high-efficiency control strategy of an induction motor. IEEE Transactions on Industry Applications, IA-22(5), 820-827.

Kisacikoglu, M. C., Ertan, H. B., & Leblebicioglu, K. (2009). Direct torque control of induction motors. IEEE Industrial Electronics Society Newsletter, 56(2), 8-20.


Directed Betweenness Centrality

Directed Betweenness Centrality (Freeman's Betweenness on Directed Graphs)

directed BC
digraph betweenness
asymmetric betweenness centrality
directed Freeman betweenness

Directed Betweenness Centrality extends Freeman's classic betweenness measure to directed graphs, quantifying how often a node lies on the shortest directed paths between all other pairs of nodes. It identifies gatekeepers, brokers, and bottlenecks in asymmetric flows such as information cascades, citation networks, and organizational hierarchies.

Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.

Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2), 163–177.

betweenness-centrality directed-degree-centrality directed-closeness-centrality directed-eigenvector-centrality directed-pagerank directed-social-network-analysis


Directed Closeness Centrality

Directed Closeness Centrality (In-closeness and Out-closeness on Directed Graphs)

directed closeness
in-closeness centrality
out-closeness centrality
directional closeness

Freeman, L. C.; Wasserman, S. & Faust, K.

Directed closeness centrality extends the classical closeness measure to directed networks by separately quantifying how quickly a node can be reached by others (in-closeness) and how quickly it can reach all others (out-closeness). It is a foundational node-level metric in social network analysis and graph theory, used wherever link direction conveys meaningful asymmetry such as citation flows, information cascades, or authority hierarchies.

Directed graph (adjacency matrix or edge list with arc direction)

Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press.

Freeman, L. C. (1979). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215–239.

closeness-centrality directed-social-network-analysis directed-betweenness-centrality directed-degree-centrality directed-eigenvector-centrality directed-pagerank


Directed Community Detection

Directed Community Detection in Networks

directed graph clustering
community detection in digraphs
directed modularity optimization
directed network partitioning

Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.

Directed community detection identifies densely interconnected groups of nodes in a directed network, accounting for the asymmetry of edges (e.g., A follows B does not imply B follows A). Adapting modularity or flow-based criteria to directed graphs reveals clusters that undirected methods systematically miss, making it essential for citation networks, follower graphs, and biological regulatory pathways.

Graph partitioning / modularity optimization

Directed graph (adjacency matrix or edge list with direction)

Leicht, E. A. & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703.

Rosvall, M. & Bergstrom, C. T. (2008). Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences, 105(4), 1118–1123.

modularity-analysis directed-social-network-analysis directed-betweenness-centrality social-network-analysis stochastic-block-model weighted-community-detection


Directed Ego Network Analysis

Directed Ego Network Analysis (Asymmetric Personal Network Mapping)

directed personal network analysis
asymmetric ego network
directed egocentric network analysis
directed egonet analysis

Barnes, J. A.; Bott, E.; extended by Everett & Borgatti

Directed ego network analysis examines the personal network of a focal node — the ego — by distinguishing the direction of each tie: who sends resources, support, or information to the ego, and to whom the ego sends them. This asymmetric perspective reveals role differentiation, dependence, and brokerage that undirected ego networks cannot capture.

Directed dyadic tie data (in/out edges from a focal node)

Everett, M. G., & Borgatti, S. P. (2005). Ego network betweenness. Social Networks, 27(1), 31–38.

Perry, B. L., Pescosolido, B. A., & Borgatti, S. P. (2018). Egocentric Network Analysis: Foundations, Methods, and Models. Cambridge University Press.

ego-network-analysis social-network-analysis directed-social-network-analysis directed-betweenness-centrality directed-degree-centrality weighted-ego-network-analysis


Directed Eigenvector Centrality

Directed Eigenvector Centrality (Asymmetric Influence Scoring on Directed Graphs)

directed EC
asymmetric eigenvector centrality
right eigenvector centrality
left eigenvector centrality

Directed eigenvector centrality extends the classic eigenvector centrality to directed graphs by scoring each node according to the centrality of the nodes that point to it (in-direction) or that it points to (out-direction). A node earns a high score not merely by having many connections but by being connected to other highly central nodes, capturing asymmetric influence in citation networks, social hierarchies, and information flows.

Centrality measure (eigenvector-based, directed)

Directed adjacency matrix / asymmetric graph

Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92(5), 1170–1182.

eigenvector-centrality directed-pagerank directed-degree-centrality directed-betweenness-centrality directed-closeness-centrality directed-social-network-analysis


Directed Exponential Random Graph Model

Directed Exponential Random Graph Model (Directed ERGM / p* Model for Directed Networks)

Directed ERGM
p-star model (directed)
directed p* model
directed Markov graph model

1986 (foundations); 2007 (modern directed ERGM formulation)

Frank, O. & Strauss, D.; extended by Robins, Pattison, Kalish & Lusher

The Directed Exponential Random Graph Model (Directed ERGM) is a family of statistical models for directed networks that estimates the probability of observing a given directed graph as a function of structural configurations — such as reciprocity, transitive triads, and in-degree centralization — and node or dyad covariates, enabling principled inference about the social processes that generate directed ties.

Statistical generative model for directed networks

Directed binary or valued adjacency matrices; node and dyad covariates

Robins, G., Pattison, P., Kalish, Y. & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2), 173-191.

Frank, O. & Strauss, D. (1986). Markov graphs. Journal of the American Statistical Association, 81(395), 832-842.

exponential-random-graph-model directed-community-detection directed-social-network-analysis stochastic-block-model directed-stochastic-block-model directed-modularity-analysis


Directed Knowledge Graph Analysis

Directed Knowledge Graph Analysis (Graph-Based Knowledge Representation and Reasoning)

directed KG analysis
knowledge graph mining
directed semantic graph analysis
KG reasoning

Hogan, A. et al. (formalized); roots in Berners-Lee, T. et al. (Semantic Web)

Directed Knowledge Graph Analysis represents factual knowledge as a directed labeled multigraph of entities (nodes) and typed relations (directed edges), enabling structured reasoning, inference, and discovery over large heterogeneous datasets. The direction of edges encodes asymmetric relationships such as 'authored-by', 'causes', or 'is-a', making the graph semantically richer than undirected alternatives.

Graph-based knowledge representation and inference

Directed labeled multigraph (subject-predicate-object triples)

Hogan, A., Blomqvist, E., Cochez, M., d'Amato, C., Melo, G. D., Gutierrez, C., ... & Polleres, A. (2021). Knowledge graphs. ACM Computing Surveys, 54(4), 1–37.

Wang, Z., Zhang, J., Feng, J., & Chen, Z. (2014). Knowledge Graph Embedding by Translating on Hyperplanes. Proceedings of the AAAI Conference on Artificial Intelligence, 28(1), 1112–1119.

knowledge-graph-analysis directed-social-network-analysis betweenness-centrality eigenvector-centrality directed-pagerank directed-community-detection


Directed Modularity Analysis

Directed Modularity Analysis (Leicht-Newman Directed Community Detection)

directed community detection via modularity

Directed modularity analysis extends the classic Newman-Girvan modularity framework to directed graphs, where edges carry a source and a destination. Formalized by Leicht and Newman in 2008, it partitions nodes into communities by maximizing a modularity score that accounts for each node's separate in-degree and out-degree in the null model, making it the standard approach for community detection in citation networks, information flows, and other asymmetric relational data.

Community detection / graph partitioning

Directed (asymmetric) adjacency matrix / edge list

Leicht, E. A., & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703.

Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.

modularity-analysis directed-community-detection directed-social-network-analysis exponential-random-graph-model stochastic-block-model betweenness-centrality


Directed Multiplex Network Analysis

Directed Multiplex Network Analysis (Multi-layer Directed Graph Framework)

directed multilayer network analysis
directed multiplex graphs
asymmetric multiplex network analysis
DMNA

Directed multiplex network analysis models systems where the same set of nodes are connected by multiple types of directed (asymmetric) relationships across distinct layers — such as citation flows, information cascades, or authority hierarchies co-existing simultaneously. It extends multiplex network analysis by preserving both layer identity and edge directionality, enabling richer structural and dynamic insights.

Multi-relational directed edge data (adjacency tensors)

Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271.

De Domenico, M., Sole-Ribalta, A., Cozzo, E., Kivela, M., Moreno, Y., Porter, M. A., Gomez, S., & Arenas, A. (2013). Mathematical formulation of multilayer networks. Physical Review X, 3(4), 041022.

multiplex-network-analysis directed-social-network-analysis directed-community-detection multilayer-network-diffusion-analysis directed-betweenness-centrality multilayer-social-network-analysis


Directed Network Diffusion Analysis

Directed Network Diffusion Analysis (Influence and Spreading Processes on Directed Graphs)

information spreading on directed networks

2003 (influence maximization formalization); epidemic models traced to Kermack & McKendrick, 1927

Kempe, D.; Kleinberg, J.; Tardos, E. (influence maximization); Pastor-Satorras, R. et al. (epidemic spreading)

Directed network diffusion analysis studies how information, disease, behavior, or influence spreads through a network in which edges carry direction — meaning transmission flows one way along each link. It combines graph-theoretic representations with stochastic spreading models such as independent cascade, linear threshold, or SIR/SIS, and is central to influence maximization, epidemic forecasting, and information propagation research.

Directed graphs with node states and edge transmission probabilities

Kempe, D., Kleinberg, J., & Tardos, E. (2003). Maximizing the spread of influence through a social network. Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 137–146.

Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015). Epidemic processes in complex networks. Reviews of Modern Physics, 87(3), 925–979.

network-diffusion-analysis social-network-analysis directed-community-detection directed-pagerank temporal-network-diffusion-analysis multiplex-network-analysis


Directed PageRank

Directed PageRank (Link-Based Authority Ranking on Directed Graphs)

PageRank
PR
Google PageRank
directed link analysis

Directed PageRank is a link-based authority scoring algorithm that assigns importance scores to nodes in a directed graph by iteratively redistributing rank through outgoing edges. Introduced by Brin and Page in 1998 as the backbone of Google Search, it measures not just how many in-links a node has but how authoritative the nodes pointing to it are.

Directed graph (adjacency list or matrix)

Brin, S. & Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine. Proceedings of the 7th International Conference on World Wide Web (WWW7), 107–117. Elsevier.

Langville, A. N. & Meyer, C. D. (2006). Google's PageRank and Beyond: The Science of Search Engine Rankings. Princeton University Press.

degree-centrality betweenness-centrality eigenvector-centrality hits-algorithm directed-social-network-analysis directed-community-detection


Directed Social Network Analysis

Directed Social Network Analysis (Digraph-Based SNA)

directed SNA
digraph analysis
directed graph network analysis
asymmetric network analysis

Directed Social Network Analysis (directed SNA) studies networks in which every tie has an explicit direction — from a sender to a receiver — rather than treating relationships as symmetric. It extends the classical SNA toolkit with in-degree, out-degree, reciprocity, and asymmetric path measures, making it the appropriate framework wherever relationship direction carries substantive meaning, such as citation flows, advice-seeking, follower graphs, or information cascades.

Directed relational / dyadic data (adjacency matrix or edge list with direction)

Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press.

Newman, M. E. J. (2010). Networks: An Introduction. Oxford University Press.

social-network-analysis betweenness-centrality degree-centrality directed-pagerank directed-community-detection exponential-random-graph-model


Directed Two-Mode Network Analysis

Directed Two-Mode (Bipartite) Network Analysis

directed bipartite network analysis
asymmetric affiliation network analysis
directed actor-event network analysis
directed two-mode graph analysis

Directed two-mode network analysis studies bipartite graphs in which nodes belong to two distinct sets — such as actors and events, authors and papers, or firms and markets — and edges carry a direction, capturing asymmetric relationships like citation, referral, or endorsement. Combining the duality of two-mode structure with directed tie semantics reveals flow patterns and influence asymmetries that undirected or single-mode analyses would miss.

Directed bipartite (two-mode) adjacency or incidence matrix

Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications (Ch. 8). Cambridge University Press.

Borgatti, S. P. & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243-269.

two-mode-network-analysis directed-social-network-analysis directed-community-detection directed-modularity-analysis multiplex-network-analysis knowledge-graph-analysis


Dirichlet Process Mixture Model

DPMM
DP mixture model
infinite mixture model
Dirichlet process mixture
nonparametric Bayesian mixture model

Ferguson (1973); mixture model formulation by Lo (1984)

The Dirichlet Process Mixture Model (DPMM) is a nonparametric Bayesian clustering method introduced through Ferguson's (1973) Dirichlet process prior that places a probability distribution over distributions. Unlike finite mixture models, the DPMM does not require the analyst to specify the number of clusters in advance; instead it infers the number of components from the data, allowing an effectively unbounded mixture that grows as more observations arrive.

density estimation / clustering / unsupervised learning

MCMC (Gibbs / collapsed Gibbs) / variational Bayes

posterior over cluster assignments, cluster parameters, and number of clusters

Ferguson, T. S. (1973). A Bayesian analysis of some nonparametric problems. The Annals of Statistics, 1(2), 209–230.

Neal, R. M. (2000). Markov chain sampling methods for Dirichlet process mixture models. Journal of Computational and Graphical Statistics, 9(2), 249–265.

Hjort, N. L., Holmes, C., Müller, P., & Walker, S. G. (Eds.) (2010). Bayesian Nonparametrics. Cambridge University Press.

bayesian-regression hierarchical-bayes mcmc latent-dirichlet-allocation gaussian-mixture-model bayesian-nonparametric-methods


Disability-Adjusted Life Year

DALY
global disease burden metric
burden of disease

Christopher J. L. Murray and Alan D. Lopez (World Health Organization / World Bank)

A DALY quantifies disease burden as the sum of years of life lost to premature death and years lived with disability. Developed by the World Health Organization and World Bank in 1990 as part of the Global Burden of Disease (GBD) study, DALYs enable epidemiologists and public health planners to compare disease burden across populations, identify health priorities, and evaluate intervention impact. One DALY = one lost year of 'healthy' life; DALYs averted measure progress toward health goals.

Murray, C. J., Lopez, A. D., & Jamison, D. T. (1994). The Global Burden of Disease in 1990: Summary Results, Sensitivity Analysis, and Future Directions. In C. J. Murray & A. D. Lopez (Eds.), Global Burden of Disease and Injury. Cambridge: Harvard University Press.

Global Burden of Disease Study 2019 Collaborators. (2020). Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1204-1222.

Mathers, C. D., Vos, T., & Lopez, A. D. (2003). The Burden of Disease and Injury in Australia. Public Health Division, Department of Health and Ageing, Australian Government.

quality-adjusted-life-year cost-effectiveness-analysis markov-model-health-economics decision-analytic-modeling willingness-to-pay


Disability Rating Scale

The Disability Rating Scale (DRS) is a brief, clinician-administered measure specifically designed to assess the severity of disability and functional recovery across the entire spectrum of traumatic brain injury (TBI)—from acute coma to community reintegration. Developed by Rappaport and colleagues in 1982, DRS has become a standard outcome measure in TBI research and clinical practice, uniquely spanning acute (comatose) phases through chronic community outcomes where other measures fail.

Rappaport, M., Hall, K. M., Hopkins, K., Belleza, T., & Cope, D. N. (1982). Disability rating scale for severe head trauma: Relation to rehabilitation outcomes. Archives of Physical Medicine and Rehabilitation, 63(3), 118–123.

Hall, K. M., Hamilton, B. B., Gordon, W. A., & Zasler, N. D. (1993). Characteristics and comparisons of functional assessment indices: Disability Rating Scale, Functional Independence Measure, and Functional Assessment Measure. Journal of Head Trauma Rehabilitation, 8(2), 60–74.

whodas-2 community-integration-questionnaire participation-measure-post-acute participation-scale impact-participation-autonomy


Disclosure Risk Assessment

Statistical Disclosure Control Risk Estimation

Istatistiksel Açıklama Riski Değerlendirmesi

Disclosure Risk Assessment is a probabilistic framework introduced by Duncan and Lambert (1989) for quantifying how likely it is that releasing microdata — individual-level records from surveys or administrative files — will allow an outside party to identify a specific respondent or infer sensitive attributes. It is used by statistical agencies, data custodians, and researchers charged with protecting confidentiality before any public release of person-level datasets.

Microdata files (individual-level records)

Output: Estimated probability of identity or attribute disclosure

Duncan, G. T., & Lambert, D. (1989). The risk of disclosure for microdata. Journal of Business & Economic Statistics, 7(2), 207–217.


Discourse Analysis in Media

Critical Discourse Analysis of Media Texts and Communication

critical discourse analysis
media discourse analysis
CDA

Language, power, and representation analysis

Discourse Analysis in Media is a method for examining how media texts use language, images, and communication patterns to construct meanings, shape identities, and perpetuate or challenge power relations. Developed from linguistic analysis and critical theory—particularly Michel Foucault's concept of discourse as a system of knowledge-production and Norman Fairclough's critical discourse analysis (CDA) framework—the method reveals how what appears as neutral information or entertainment actually participates in maintaining or challenging social hierarchies and ideologies. The method is specifically concerned with how discourse operates politically: what it makes possible to think and say, whom it privileges, and what alternatives it renders invisible.

Method for examining how discourse in media constructs meaning, identity, and power relations

Fairclough, N. (1992). Discourse and Social Change. Polity Press.

Foucault, M. (1980). Power/Knowledge: Selected Interviews and Other Writings 1972-1977. Pantheon Books.

Van Dijk, T. A. (2015). Critical Discourse Studies: A Sociocognitive Approach. In R. Wodak & M. Meyer (Eds.), Methods of Critical Discourse Studies (3rd ed., pp. 62-86). SAGE.

Wodak, R., & Meyer, M. (2009). Critical Discourse Analysis: History, Agenda, Theory and Methodology. In R. Wodak & M. Meyer (Eds.), Methods of Critical Discourse Analysis (2nd ed., pp. 1-33). SAGE.

media-framing-analysis visual-content-analysis film-narrative-analysis agenda-setting-analysis reception-analysis


Discourse Analysis

DA
Critical Discourse Analysis
Discursive Analysis

1989 (Fairclough); 1987 (Potter & Wetherell)

Norman Fairclough; Jonathan Potter and Margaret Wetherell

Discourse analysis is a qualitative research methodology that examines how language, communication, and power shape meaning, identity, and social reality. Developed across linguistics, sociology, and psychology (particularly by Norman Fairclough and Jonathan Potter), discourse analysis goes beyond content to analyze language use as a social practice that constitutes and reflects power relations, ideologies, and social structures.

Fairclough, N. (1989). Language and power. Longman.

Potter, J., & Wetherell, M. (1987). Discourse and social psychology: Beyond attitudes and behaviour. Sage Publications.

Machin, D., & Mayr, A. (2012). How to do critical discourse analysis: A multimodal introduction. Sage Publications.

content-analysis-qualitative rhetoric-analysis critical-discourse-analysis linguistic-analysis power-language


Discourse Parsing

Discourse Parsing (Rhetorical Structure Analysis)

rhetorical structure analysis
RST parsing
PDTB parsing
Söylem Ayrıştırma (Discourse Parsing)

Mann & Thompson (RST); Prasad et al. (PDTB)

Discourse parsing is a natural-language-processing task that models the rhetorical relations between sentences and paragraphs of a text — relations such as cause, contrast, and elaboration — and represents them as a tree structure. It works within established frameworks, principally Rhetorical Structure Theory (RST), introduced by Mann and Thompson in 1988, and the Penn Discourse TreeBank (PDTB), released by Prasad and colleagues in 2008.

Rhetorical Structure Theory (RST) / Penn Discourse TreeBank (PDTB)

Output: Discourse tree of rhetorical relations (e.g. cause, contrast, elaboration)

Mann, W. C. & Thompson, S. A. (1988). Rhetorical Structure Theory: Toward a functional theory of text organization. Text, 8(3), 243-281.

Prasad, R., Dinesh, N., Lee, A., Miltsakaki, E., Robaldo, L., Joshi, A. & Webber, B. (2008). The Penn Discourse TreeBank 2.0. Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC 2008).


Discrete Choice Simulation

Discrete Choice Simulation (Stated Preference / SP Simulation)

Ayrık Seçim Simülasyonu (Stated Preference / SP Simulation)

1974 (McFadden's Nobel-cited logit); simulation extensions throughout 1990s–2000s

Daniel McFadden (random utility theory); Kenneth Train (simulation methods)

Discrete choice simulation is a behavioural modelling method — grounded in random utility theory formalised by Daniel McFadden in the 1970s and extended to simulation-based estimation by Kenneth Train — that estimates how individuals choose among mutually exclusive alternatives and then uses those estimated preference parameters to forecast how choice shares would shift under hypothetical policy or market scenarios. It is the dominant quantitative tool in transport demand analysis, health economics, environmental valuation, and marketing research.

Discrete choice modelling with Monte Carlo simulation

Multinomial logit (MNL), nested logit, mixed logit (random parameters logit)

Orthogonal or D-optimal choice experiment design

Utility-function coefficients, choice probabilities, willingness-to-pay (WTP), market-share forecasts

Transport, health economics, marketing, environmental valuation

Train, K.E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press.

Ben-Akiva, M. & Lerman, S.R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press.

microsimulation conjoint-analysis multinomial-logit mixed-logit agent-based-modelling monte-carlo-simulation


Discrete-Event Simulation

DES
event-driven simulation
Ayrık Olay Simülasyonu (DES)

1960s (formalized); modern computational form from 1970s onward

Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)

Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time.

Event-driven (state changes occur only at discrete event times)

Output: Performance metrics — throughput, waiting times, resource utilization, queue lengths

Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson.

Law, A.M. (2015). Simulation Modeling and Analysis (5th ed.). McGraw-Hill.

system-dynamics monte-carlo-simulation latin-hypercube-sampling agent-based-modeling queuing-theory


Discrete-Event System Simulation

Discrete-Event System Simulation (Arena / AnyLogic style)

Kesikli Sistem Simülasyonu (Arena / AnyLogic tarzı)

1960s (formalised in literature through the 1980s–2000s)

Kelton, Law & Sadowski (formalised methodology); SIMSCRIPT (Markowitz et al., 1963) and GPSS (Gordon, 1961) were pioneering tools

Discrete-event system simulation (DES) is a computational modelling technique in which the state of a system changes only at discrete points in time — called events — such as a customer arriving, a machine starting, or a job completing. Formalised through foundational texts by Kelton, Sadowski, and Zupick (2014) and Law (2015), DES represents processes as networks of resources, queues, and activities, allowing analysts to test capacity and policy changes on a virtual model before touching the real system.

Discrete-event (state changes only at event times)

Manufacturing, service systems, supply chain, healthcare logistics

Output: Throughput, queue lengths, resource utilisation, cycle times under simulated scenarios

Kelton, W.D., Sadowski, R.P. & Zupick, N.B. (2014). Simulation with Arena (6th ed.). McGraw-Hill.

monte-carlo-simulation agent-based-modeling system-dynamics queuing-theory bootstrap-simulation


Discrete Wavelet Transform

The discrete wavelet transform (DWT) is a fast, computationally efficient method for decomposing signals into different frequency and time components using orthogonal or biorthogonal wavelet functions. Developed rigorously by Ingrid Daubechies (1992) and built on Mallat's multiresolution decomposition theory (1989), the DWT employs filter banks to recursively split a signal into approximation (low-frequency) and detail (high-frequency) components. It has become the foundation for signal processing applications ranging from compression to feature extraction.

Daubechies, I. (1992). Ten Lectures on Wavelets. SIAM.

Mallat, S. G. (1989). A theory of multiresolution signal decomposition: The wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7), 674–693.

Walnut, D. F. (2002). An Introduction to Wavelet Analysis. Birkhäuser.

continuous-wavelet-transform modwt stationary-wavelet-transform fast-fourier-transform


Discriminant Analysis

LDA
Fisher discriminant analysis
discriminant function analysis
canonical discriminant analysis

Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error.

Supervised classification and dimension reduction

Continuous predictors, categorical group membership

Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.

Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning.

principal-component-analysis logistic-regression cluster-analysis confirmatory-factor-analysis canonical-correlation-analysis multivariate-analysis-of-variance


Discriminant Validity

discriminant validity evidence
divergent validity
DV
AVE-based discriminant validity

Discriminant validity is evidence that a latent construct is empirically distinct from other constructs it should differ from. Originating in Campbell and Fiske's multitrait-multimethod framework (1959), it is a core component of construct validity and a mandatory check in scale development and structural equation modeling.

Validity evidence / psychometric evaluation

Latent construct scores, item-level responses, correlation/covariance matrices

Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

convergent-validity construct-validity confirmatory-factor-analysis exploratory-factor-analysis cronbachs-alpha measurement-invariance


DGS

The Disenfranchised Grief Scale (DGS), developed from Kenneth J. Doka's conceptual framework, assesses grief that society does not recognize, validate, or support—grief that is excluded from public mourning rituals, openly acknowledged grief ceremonies, or institutional support. Examples include loss of a former spouse, affair partner, ex-partner, friend (not family), pet, or pregnancy loss. The DGS captures the unique burden of grieving without social permission or recognition.

Doka, K. J. (Ed.). (2002). Disenfranchised grief: New directions, challenges, and strategies for practice. Research Press.

inventory-complicated-grief grief-experience-questionnaire texas-revised-inventory-grief adult-attitude-to-grief


Disproportional cluster sampling

disproportionate cluster sampling
unequal-probability cluster sampling
variable-rate cluster sampling
non-proportional cluster sampling

Mid-20th century (formalised 1950s–1965)

Disproportional cluster sampling is a probability-based survey design in which naturally occurring groups (clusters) are selected as primary sampling units, but the number of clusters or elements drawn from each group is not proportional to that group's share of the population. By deliberately over- or under-sampling certain clusters, researchers gain analytic flexibility and precision where it matters most, at the cost of requiring post-hoc weighting for population-level inference.

Quantitative / population-level survey data

Kish, L. (1965). Survey Sampling. John Wiley & Sons.

Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons.

cluster-sampling proportional-cluster-sampling disproportional-stratified-sampling multistage-sampling weighted-sampling systematic-sampling


Disproportional Stratified Sampling

Disproportional Stratified Random Sampling

disproportionate stratified sampling
unequal-probability stratified sampling
oversampling stratified design
non-proportional stratified sampling

Disproportional stratified sampling divides the population into mutually exclusive strata and deliberately draws different proportions from each stratum — oversampling small or analytically important subgroups and undersampling large ones. Post-hoc weighting restores population-level representativeness when overall estimates are needed. First formalised by Jerzy Neyman in 1934, it is the standard approach when subgroup-level precision matters as much as total-population estimates.

Quantitative or mixed; structured survey or administrative records data

Neyman, J. (1934). On the two different aspects of the representative method: The method of stratified sampling and the method of purposive selection. Journal of the Royal Statistical Society, 97(4), 558-625.

proportional-stratified-sampling stratified-sampling cluster-sampling multistage-sampling weighted-sampling simple-random-sampling


Dissociative Experiences Scale

Dissociative symptom severity assessment

The DES is a 28-item self-report questionnaire designed to measure the frequency and severity of dissociative symptoms, including depersonalization (feeling detached from one's body), derealization (feeling the world is unreal), amnesia, absorption (intense focus), and identity confusion. Developed by Bernstein and Putnam in 1986, it is the most widely used dissociation screening instrument in clinical and research settings. The DES helps identify dissociative disorders (dissociative identity disorder, other specified dissociative disorder), trauma-related dissociation, and dissociative symptoms in other psychiatric conditions.

Bernstein, E. M., & Putnam, F. W. (1986). Development, reliability, and validity of a dissociation scale. Journal of Nervous and Mental Disease, 174(12), 727–735.

Putnam, F. W., Carlson, E. B., Ross, C. A., Torem, M., Shi, Y., Fielding, S., & Elterman, E. (1996). Patterns of dissociation in clinical and nonclinical samples. Journal of Nervous and Mental Disease, 184(11), 673–679.

Carlson, E. B., Putnam, F. W., Ross, C. A., Torem, M., Coons, P., Bowman, E. S., ... & Spiegel, D. (2011). Features and outcome of 34 patients with dissociative identity disorder. Journal of Nervous and Mental Disease, 199(8), 632–645.


Dissolution f1/f2 Similarity

The f1 and f2 factors are dimensionless statistical measures developed by Moore and Flanner to quantify the similarity between two dissolution profiles. Adopted by regulatory agencies (FDA, EMA) as the gold standard for comparing dissolution curves, these factors enable rapid assessment of whether formulation changes significantly impact drug release.

Moore, J. W., & Flanner, H. H. (1996). Mathematical comparison of dissolution profiles. Pharmaceutical Technology, 20(6), 64-74.

Shah, V. P., Tsong, Y., Sathe, P., & Liu, J. P. (1998). In vitro dissolution profile comparison--statistics and analysis of the similarity factor, f2. Pharmaceutical Research, 15(6), 889-896.


DIST-CHEBYSHEV

DIST-CHEBYSHEV (Chebyshev Distance — L∞ norm (maximum coordinate difference)) is a distance multi-criteria decision-making (MCDM) method introduced by Roy, B. in 1991. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Roy, B. (1991). Chebyshev Distance. Journal of Multi-Criteria Decision Analysis


DIST-EUCLIDEAN

DIST-EUCLIDEAN (Euclidean Distance — L2 norm between two vectors in criterion space) is a distance multi-criteria decision-making (MCDM) method introduced by Hwang, C. L., Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag


DIST-HAMMING

DIST-HAMMING (Hamming Distance — count of positions where two equal-length sequences differ) is a distance multi-criteria decision-making (MCDM) method introduced by Hamming, R. W. in 1950. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Distance (categorical, count of differing positions)

Hamming, R. W. (1950). Hamming Distance. Bell System Technical Journal


DIST-MANHATTAN

DIST-MANHATTAN (Manhattan Distance — L1 norm (city-block distance) between two vectors) is a distance multi-criteria decision-making (MCDM) method introduced by Dezert, J., Tchamova, A., Han, D., Bhotto, M. Z. A. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Dezert, J., Tchamova, A., Han, D., Bhotto, M. Z. A. (2020). Manhattan Distance. IEEE Transactions on Cybernetics


DIST-MINKOWSKI

DIST-MINKOWSKI (Minkowski Distance — generalised Lp norm (p ≥ 1)) is a distance multi-criteria decision-making (MCDM) method introduced by Minkowski, H. in 1910. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Minkowski, H. (1910). Geometrie der Zahlen. Teubner, Leipzig


Distance Sampling

Distance Sampling for Estimating Abundance

line transect
point transect
distance estimation
detection probability

Distance sampling is a statistical method for estimating population abundance from data on distances between observers and detected individuals. Developed by Buckland and colleagues (1993) and formalized in the software Distance, this approach accounts for imperfect detection: animals far from an observer are less likely to be detected. By modeling the detection function (probability of detecting an animal at various distances), distance sampling produces unbiased estimates of abundance and density even when detection is incomplete.

Buckland, S. T., Anderson, D. R., Burnham, K. P., Laake, J. L., Borchers, D. L., & Thomas, L. (1993). Distance Sampling: Estimating Abundance of Biological Populations. Chapman and Hall, London.

Thomas, L., Buckland, S. T., Rexstad, E. A., et al. (2010). Distance software: design and analysis of distance sampling surveys for estimating population size. Journal of Applied Ecology, 47(1), 5-14.

Buckland, S. T., Anderson, D. R., Burnham, K. P., Laake, J. L., Borchers, D. L., & Thomas, L. (2001). Introduction to Distance Sampling. Oxford University Press.

species-accumulation population-viability-analysis food-web-topology leslie-matrix


DHI

The Dizziness Handicap Inventory (DHI) is a 25-item self-report questionnaire designed to measure the functional, emotional, and physical effects of dizziness and balance disorders on daily life. Developed by Jacobson and Newman in 1990, it has become a standard tool for assessing dizziness-related handicap in clinical and research settings. The DHI is valuable for tracking disability progression and treatment response in vestibular patients.

Jacobson, G. P., & Newman, C. W. (1990). The development of the Dizziness Handicap Inventory. Archives of Otolaryngology - Head & Neck Surgery, 116(4), 424-427.


DLinear

DLinear (Decomposition Linear Model for Forecasting)

Decomposition Linear
DLinear Forecaster
Linear Decomposition Model
Ayrışım Doğrusal Modeli

DLinear is a lightweight time series forecasting model introduced by Zeng et al. at AAAI 2023. It challenges the prevailing assumption that Transformer-based architectures are necessary for accurate long-horizon forecasting. The model decomposes an input sequence into trend and seasonal components using a moving average filter, then applies separate single-layer linear transformations to each component before summing their outputs to produce the final forecast.

Decomposition-based linear forecasting model

Input: Univariate or multivariate time series

Output: Multi-step ahead point forecasts

Zeng, A., Chen, M., Zhang, L., & Xu, Q. (2023). Are transformers effective for time series forecasting? AAAI.


DLQI

DLQI
Finlay Index
Dermatology Quality of Life

The DLQI is the primary patient-centered outcome measure in dermatology research and clinical practice. Developed by Andrew Finlay and Gul Khan in 1994, this 10-item self-report questionnaire quantifies the impact of skin disease on patients' daily functioning, emotional well-being, social relationships, and work capacity. It is simple, rapid, and applicable to virtually all dermatological conditions, making it the gold standard for assessing quality of life in dermatology.

Self-report quality of life questionnaire

Finlay, A. Y., & Khan, G. K. (1994). Dermatology Life Quality Index (DLQI): A simple practical measure for routine clinical use. Clinical and Experimental Dermatology, 19(3), 210-216.

Hongbo, Y., Thomas, C. L., Harrison, M. A., Salek, M. S., & Finlay, A. Y. (2005). Translating the science of quality of life into practice: What do dermatology patients' need? Dermatologic Clinics, 23(4), 675-684.

Basra, M. K., Fenech, R., Gatt, R. M., Salek, M. S., & Finlay, A. Y. (2008). The Dermatology Life Quality Index 1994-2007: A review of instrument evolution and application. British Journal of Dermatology, 159(5), 997-1035.


DMFT Index

DMFT (Decayed, Missing, Filled Teeth) Index

Henry Klein, Cedric Palmer, and James Knutson

The DMFT (Decayed, Missing due to caries, Filled) Index is a standardized epidemiological measure of dental caries experience in permanent dentition. Developed by Klein, Palmer, and Knutson in 1938, it quantifies the number of permanent teeth that are decayed, missing due to caries, or filled due to caries. The DMFT Index remains the most widely used caries index globally, enabling comparison of oral health across populations and tracking disease burden over time.

Klein, H., Palmer, C. E., & Knutson, J. W. (1938). Studies on dental caries: I. Dental status and dental needs of elementary school children. Public Health Reports, 53(32), 1259-1274.

World Health Organization. (2013). Oral health surveys: Basic methods (5th ed.). WHO.

Pitts, N. B., Zero, D. T., Marsh, P. D., et al. (2017). Dental caries. Nature Reviews Disease Primers, 3, 17030.

periodontal-probing oral-hygiene-index gingival-index dental-erosion-index bone-density-dental


DMRG

DMRG
density matrix renormalization
tensor network

Density Matrix Renormalization Group (DMRG) is a powerful computational method for solving strongly correlated quantum systems, particularly one-dimensional lattice models and quantum chemistry problems. Introduced by White in 1992, DMRG uses a variational approach and tensor-network representation to efficiently describe quantum ground states and excitations, achieving numerical accuracy competitive with exact diagonalization for systems that other methods cannot treat.

White, S. R. (1992). Density matrix formulation for quantum renormalization groups. Physical Review Letters, 69(19), 2863-2866.

Schollwöck, U. (2005). The density-matrix renormalization group in the age of matrix product states. Reviews of Modern Physics, 77(1), 259-315.


DNMA

DNMA (Double Normalization-Based Multiple Aggregation) is a ranking multi-criteria decision-making (MCDM) method introduced by Liao, H., Wu, X. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Dual-normalisation aggregation (linear + vector)

Liao, H., Wu, X. (2020). DNMA: A double normalization-based multiple aggregation method for multi-expert multi-criteria decision making. Omega

ahp anp bwm bwm-bayesian ccsd cilos cimas critic


Directory of Open Access Journals

DOAJ Community (Swedish library consortium, later expanded to international consortium)

The Directory of Open Access Journals (DOAJ) is a community-maintained, freely accessible directory of high-quality, peer-reviewed open-access journals and articles established in 2003. DOAJ indexes over 20,000 open-access journals across all disciplines (sciences, social sciences, humanities, arts) from diverse geographic regions. The directory serves researchers, librarians, and administrators as the authoritative curated list of legitimate open-access journals—differentiating quality open-access publications from predatory journals that lack genuine peer review. DOAJ quality seal, awarded to journals meeting stricter governance and transparency criteria, enables identification of the highest-caliber open-access publications.

Directory of Open Access Journals. (2024). About DOAJ. Retrieved from https://doaj.org/

Laakso, M., Welling, P., Bukvova, H., Nyman, L., Björk, B. C., & Hedlund, T. (2011). The development of open access journal publishing 1993–2009. PLoS ONE, 6(6), e20961.

Solomon, D. J., & Björk, B. C. (2012). A study of open access journals using article processing charges. Journal of the American Society for Information Science and Technology, 63(8), 1485-1495.

web-of-science scopus-database impact-factor pubmed-medline ulrichsweb


Doc2Vec Document Embeddings (Paragraph Vector)

paragraph vector
document embeddings
Doc2Vec Belge Gömülmeleri

Doc2Vec, also known as Paragraph Vector, is a representation-learning method introduced by Le and Mikolov (2014) that maps whole documents to fixed-length dense vectors. These vectors place similar documents close together in space, supporting document comparison and classification.

Output: Fixed-length dense vector per document

Le, Q. V. & Mikolov, T. (2014). Distributed Representations of Sentences and Documents. Proceedings of the 31st International Conference on Machine Learning (ICML), 1188-1196.

glove-embeddings tf-idf text-classification sentiment-analysis


Doctrinal Legal Research

black-letter law research
legal doctrine analysis
analytical jurisprudence
traditional legal scholarship

19th century (systematised ~1860s–1880s in common law jurisdictions)

Common law tradition; systematised by jurists such as A.V. Dicey and John Austin

Doctrinal legal research is the foundational methodology of legal scholarship. It systematically identifies, reads, and analyses authoritative legal sources — statutes, case law, constitutional texts, and regulations — to describe, explain, and critique the content and internal logic of legal doctrine. By working within the accepted hierarchy of legal sources, it answers the question 'What is the law?' with analytical rigour and interpretive precision, producing descriptions of settled doctrine and arguments for how ambiguities should be resolved.

Primary legal sources (statutes, case law, regulations) and secondary sources (legal commentary, treatises)

Hutchinson, T. (2013). Researching and Writing in Law (3rd ed.). Thomson Reuters.

MacCormick, N. (2005). Rhetoric and the Rule of Law: A Theory of Legal Reasoning. Oxford University Press.

comparative-legal-analysis case-law-analysis legal-content-analysis hermeneutic-analysis textual-criticism historical-archival-research


Document Analysis

Systematic Analysis of Primary and Secondary Documents

documentary analysis
textual analysis
content analysis of documents
archival research

Document analysis is a systematic qualitative research method for examining written, visual, or audiovisual sources—such as policy documents, historical records, organizational records, media reports, emails, social media posts, photographs, or videos—to extract meaning, identify patterns, and understand social phenomena. Developed by Weber and Mannheim in early 20th-century sociology, the method bridges historical research, content analysis, and textual interpretation. Document analysis is used across disciplines to understand organizational change, policy evolution, media representation, historical events, and cultural meaning. Documents provide evidence of what organizations, institutions, or societies value, decide, and communicate, often revealing contradictions between policy and practice.

Scott, J. (1990). A Matter of Record: Documentary Sources in Social Research. Polity Press.

Prior, L. (2003). Using Documents in Social Research. SAGE Publications.

Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27-40.

Flick, U. (2014). An Introduction to Qualitative Research (5th ed.). SAGE Publications.

participant-observation qualitative-synthesis-methods nvivo-atlas-qualitative qualitative-rigor-criteria


Document-based Curriculum Analysis

curriculum document analysis
curricular document review
document analysis of curriculum
DCA

1950s–1980s (consolidated as a distinct approach)

Rooted in curriculum theory (Tyler, 1949) and document analysis methodology (Bowen, 2009)

Document-based curriculum analysis is a qualitative research method that systematically examines written curriculum artifacts — textbooks, syllabi, national standards, policy documents, scope-and-sequence guides, and lesson frameworks — to reveal intended learning goals, ideological assumptions, gaps, and alignment between policy and practice. It treats curriculum documents as primary data rather than supplementary material, applying structured content and interpretive analysis techniques to answer questions about what knowledge is valued, how it is sequenced, and whose perspectives are represented.

Curriculum documents: textbooks, syllabi, standards, policy documents, lesson plans, scope-and-sequence guides

Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40.

McCutcheon, G. (1982). What in the world is curriculum theory? Theory Into Practice, 21(1), 18–22.

curriculum-analysis document-analysis textual-criticism content-analysis comparative-curriculum-analysis policy-analysis


Document-based Program Evaluation

documentary program evaluation
records-based evaluation
document review evaluation
archival program evaluation

1960s–1970s (program evaluation field); document review as formal strategy codified in 1980s–1990s

Daniel Stufflebeam; Peter Rossi and Howard Freeman (systematic program evaluation tradition)

Document-based program evaluation is a systematic approach to assessing a program's design, implementation, and outcomes using existing documentary evidence — such as policy statements, implementation reports, budgets, meeting minutes, and program artifacts — rather than primary data collection through interviews or observation. It is particularly suited to retrospective evaluations, accountability reviews, and contexts where direct fieldwork is impractical or infeasible.

Program records, policy documents, reports, meeting minutes, budgets, artifacts

Stufflebeam, D. L., & Shinkfield, A. J. (2007). Evaluation Theory, Models, and Applications. Jossey-Bass.

Rossi, P. H., Lipsey, M. W., & Freeman, H. E. (2004). Evaluation: A Systematic Approach (7th ed.). Sage.

program-evaluation document-analysis content-analysis curriculum-analysis historical-archival-research case-law-analysis


Document Clustering

text clustering
unsupervised text grouping
Belge Kümeleme (Document Clustering)

Document clustering is an unsupervised text-mining task that groups documents with similar content together without using any labels. It is used to organise large collections and for exploratory analysis, drawing on the body of text-mining techniques consolidated by Aggarwal and Zhai (2012) and compared empirically by Steinbach, Karypis and Kumar (2000).

Input: Vectorised document collection

Output: Cluster assignment per document

Aggarwal, C. C. & Zhai, C. (2012). Mining Text Data. Springer.

Steinbach, M., Karypis, G. & Kumar, V. (2000). A Comparison of Document Clustering Techniques. KDD Workshop on Text Mining.

topic-modeling tf-idf keyword-extraction thematic-analysis


Document Collection

document analysis
documentary method
document review
secondary document analysis

19th–20th century historical methods; contemporary social-science codification c. 2000s

Rooted in historical and social science traditions; systematized by Lindsay Prior and Glenn Bowen

Document collection is a systematic data-collection technique in which the researcher gathers and reviews existing written, visual, or digital records — such as reports, meeting minutes, policies, letters, photographs, or institutional records — as primary or supplementary evidence. It is widely used in qualitative, historical, and mixed-methods research and can stand alone or complement interviews and observation.

Qualitative / mixed data-collection technique

Existing written, visual, or digital documents (reports, records, correspondence, policies)

Prior, L. (2003). Using Documents in Social Research. Sage.

content-analysis archival-research secondary-data-analysis discourse-analysis systematic-review thematic-analysis


DODGSON

DODGSON (Dodgson Method — Condorcet completion by minimum pairwise swaps) is a aggregationoperator multi-criteria decision-making (MCDM) method introduced by Dodgson, C. L. in 1900. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Pairwise-swap distance — alternative needing fewest swaps to become Condorcet winner

Dodgson, C. L. (1900). A method of taking votes on more than two issues (1876). Pamphlet, Clarendon Press, Oxford (original 1876)