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Published February 7, 2023 | Version 1.0
Dataset Restricted

TRACES Bulgarian Telegram Dataset Annotated with Linguistic Markers of Lies

  • 1. Gate Institute
  • 2. GATE Institute

Description

This dataset has been created within Project TRACES (more information: https://traces.gate-ai.eu/). The dataset contains 8791 anonymized Telegram social media posts, written in Bulgarian. The dataset is annotated with general information (named entities, part-of-speech tags, sentence length, etc.) and specific markers signaling details and can be used for general purposes or for building lies, manipulation, and disinformation detection applications.

Note: this dataset is not fact-checked, the social media messages have been retrieved via keywords. For fact-checked datasets, see our other datasets.

The social media posts have been collected via Telegram Desktop in June-July 2022.

Explanations of which fields can be used as markers of lies (or of intentional disinformation) are provided in our forthcoming paper: 

Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology
Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.

Notes

The project TRACES has indirectly received funding from the European Union's Horizon 2020 research and innovation action programme, via the AI4Media Open Call #1 issued and executed under the AI4Media project (Grant Agreement no. 951911).

 

This dataset is shared with the License: Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0).

We forbid the use of these texts for:

  • user profiling

The Project Sponsors (European Commission and the AI4Media project), Researchers, users or subjects shall not be liable or otherwise responsible for any damages (including pecuniary or moral damages) arising out or in relation to the uses of this resource.

When using this resource, please cite this article:

Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.

Files

Restricted

The record is publicly accessible, but files are restricted to users with access.

Request access

If you would like to request access to these files, please fill out the form below.

You need to satisfy these conditions in order for this request to be accepted:

Conditions:

This dataset is provided under Creative Commons Attribution 4.0 International (CC BY 4) with the additional terms below. 

Please describe the entity you are applying from (if it exists - e.g. academic institution, company, government agency), and your intended use of the dataset. The TRACES team members will review your application and you may be granted access or not.

If you have questions, please contact us at: irina.temnikova@gmail.com

In order to be allowed access to this dataset, in line with applicable legislation, including but not limited to the General Data Protection Regulation (GDPR), the Artificial Intelligence Act (AI Act, current draft as of 01 November 2022, pending adoption and entry into force), and the TRACES Project Data Management Plan, if you want to download or use this dataset, you must agree with and abide with the following terms and conditions:

  • The dataset is anonymized, and all personal information revealing the authors is removed. The dataset cannot be used for profiling Telegram users or for any applications, which breach the AI Act’s provisions. The identity reconstruction of the authors of the social media dataset is forbidden.

  • Upon request of the authors of the Telegram posts or of the TRACES team, specific posts and their annotations must be deleted.

  • The social media posts, included in this dataset, are annotated with linguistic markers *potentially* signaling lies. The presence of such markers should not indicate that the social media posts contain disinformation, misinformation, lies, untrue facts and/or other inconsistencies with 100% confidence, but with a lower degree of confidence (certain likelihood, but not certainty).

  • The linguistic markers are currently being developed and are provided purely and solely for scientific purposes. They cannot be used as conclusive evidence, as evidence in judicial or administrative proceedings, or in any other way not directly related to Project TRACES.

  • No legal action should or could be taken against the authors of the social media posts, included in the dataset, solely based on the presence of linguistic markers, potentially signaling lies.

  • The dataset is not suitable to be used and shall not be used for governmental or public authority purposes, including for investigations, government surveillance, intelligence work, analysis, criminal investigation, court or administrative proceedings. 

  • The presence of linguistic markers of potential lies in social media posts are not statements/beliefs/affirmations of the Project's team members or affiliated institutions. 

  • The Project Sponsors (AI4Media, F6S, and the European Commission), the members of the TRACES team, users or subjects shall not be liable or otherwise responsible for any consequences and/or damages (including pecuniary or moral damages) arising out of or in relation to the Project, the data collected, and the methods used for their analysis and/or the results/outcomes.

  • This notice, as well as all the activities of the TRACES Project and of its Project Sponsors, team members, users or subjects, including any contractual and/or non-contractual liability, are governed exclusively by the European Union laws and by the laws of the Republic of Bulgaria.

You agree to provide attribution to the TRACES project in the following format:

The TRACES project (https://traces.gate-ai.eu/):

Dataset name: TRACES_Dts9.1.1_socialmedia_AutomaticAnnTelegram_1

Data source: Telegram.

Research article to cite: Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.

Link to the original dataset: https://zenodo.org/record/7614294

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Additional details

Funding

AI4Media – A European Excellence Centre for Media, Society and Democracy 951911
European Commission