Data curation strategies to support responsible big social research and big social data reuse

This lightning talk responds to the question: how can data curators support responsible use and reuse of big social data? Big social research repurposes existing data from online sources such as social media, blogs, or forums, with a goal of advancing knowledge of human behavior and social phenomena. Big social research also presents an array of challenges—for example, challenges relating to context, informed consent, privacy, and intellectual property. Partly because of these challenges, big social data are less commonly shared in data repositories than other types of data, and they are on the periphery of data sharing and data reuse conversations.

This talk presents the results of a study that aims to understand the data curation implications of big social research. The study identifies key challenges and strategies for responsible research practice and data curation through a review of the literature and interviews with curators and researchers. A key takeaway from the study is that we are in need of more concrete guidance for big social research. Institutional review boards, which act as the main compliance bodies in the United States, grant exempt status to most research involving secondary analysis, data reuse, or data scraping. Interviewees often reported cobbling together strategies for responsible practice from many sources—weighing benefits and risks in their own minds, talking to colleagues and collaborators, reading other studies, and implementing strategies they learned in graduate school. It was rare for interviewees to discuss standardized ethical guidelines or clear community best practices. 

The talk concludes with implications for data curation practice. For example, this study shows that data curation strategies such as metadata and description can communicate context and data quality to future users, and standardized metadata and file formats can support data aggregation and comparability. Data curators can also support big social research and big social data reuse by considering how informed consent and privacy were addressed by the social media platform and the research design. If data curators can reach researchers early in the research process, they can support sharing and reuse by advising on a variety of challenges during the research design phase. Data repositories can also be designed to support big social data reuse by providing analysis tools that do not require sharing the full big social dataset. 

Ultimately, this lightning talk provides strategies for data curators to support responsible use and sharing for big social data. Supporting responsible practices for using these data can help scale up social science research, thus enhancing our understanding of human behavior and social phenomena.