Call for Abstracts: Sustainable archiving, exploitation, distribution of social media data



Conference from 19 - 20 March 2024 at the German National Library (Frankfurt am Main)
Website: DNB - Web archiving - Call for Papers: "Sustainable archiving of social media data - Twitter and beyond"

Social media is both a source of data for and the focus of a range of research approaches in the humanities, social sciences, IT, sciences and life sciences. The development of social media over time makes it a part of our digital cultural heritage, but the process for institutions to archive and document these in ways which fully reflect its detail and complexity is still only rudimentary. One key reason for this is the unique characteristics of the data in terms of media technology, economics, social factors and aesthetics. This confronts researchers, research institutions and cultural heritage institutions with many different challenges in terms of how to archive, catalogue and provide the data for later use. One example of this is Twitter (now known as “X”). The monetisation of the platform’s internal archive (part of ongoing restructuring of the platform) has had a radical impact on research and archiving. While flexible APIs and access opportunities before early 2023 led to a boom in research activity and the creation of comprehensive collections, access for research and archive has been made increasingly difficult since then.

Archiving, cataloguing and providing dynamic data from social media present challenges which affect researchers, research institutions, libraries and archives in equal measure, and the best way to solve these problems is through collaboration and partnership. This requires wide-ranging efforts which would be impossible for a single data community or discipline. The aim of the conference is to facilitate networking between libraries, archives, research institutes and researchers in German-speaking countries who are involved in archiving and long-term use of data and digital objects from social media.

Conference presentations should focus on the following topics:
• The interaction between research and archiving
• Research data problems in Tweet-based research caused by the loss of Twitter as a data provider
• The status and maintenance of social media from an archival and cultural-historical perspective, e.g. posts, interactions and platform elements
• The consolidation of collections, corpora, and holdings such as metadata
• Initiatives to encourage archiving and cataloguing of social media data
• Concepts for providing derivative datasets from social media and how these can be used
• Ethical questions
• Legal issues
• The possibility of creating a social media data registry

Please submit your abstract (max. 1 page / 500 words) and no more than 1 page of biobibliographic data as a PDF in German or English. Up to 20 minutes are available for each presentation, plus 10 minutes for discussion.

Submission to:

Deadline for submission of abstracts: 31 October 2023
feedback on acceptance of paper: 30 November 2023

The conference will take place from about noon, 19 March 2024 and end in the early evening of 20 March. It will be followed by a data sprint working with a long-term corpus of German Twitter data on 21 & 22 March 2024.
More information coming soon.

Conference: 19. - 20. March 2024
Data Sprint: 21. - 22. March 2023

Venue: German National Library, Frankfurt am Main

Speakers who do not have their own resources for travel may apply for up to €300 to cover travel and accommodation costs.

Organisation: Dr. Britta Woldering, Letitia Mölck, German National Library,

Programme Committee (in alphabetical order)

Stefan Dietze (Heinrich Heine University Düsseldorf)
Dimitar Dimitrov (GESIS)
Christoph Eggersglüß (Philipps University Marburg, NFDI4Culture)
Philippe Genêt (German National Library, Text+)
Tatjana Scheffler (Ruhr University Bochum)
Claus-Michael Schlesinger (University Library, Humboldt University Berlin)
Britta Woldering (German National Library)

Cooperation partners:

Deutsche Nationalbibliothek
NFDI4Data Science