Archiving information from geotagged tweets to promote reproducibility and comparability in social media research

Abstract

Sharing social media research datasets allows for reproducibility and peer-review, but it is very often difficult or even impossible to achieve due to legal restrictions and can also be ethically questionable. What is more, research data repositories and other research infrastructure and research support institutions are only starting to target social media researchers. In this paper, we present a practical solution to sharing social media data with the help of a social science data archive. Our aim is to contribute to the effort of enhancing comparability and reproducibility in social media research by taking some first steps towards setting standards for sustainable data archiving. We present a showcase for sharing social media data with the example of a big dataset containing geotagged tweets (several months of continued geotagged tweets from the United States from 2014 and 2015; nearly half a billion tweets in total) through a research data archive. We provide a general background to the process of long-term archiving of research data. After some consideration of the current obstacles for sharing and archiving social media data, we present our solution of archiving the specific dataset of geotagged tweets at the GESIS Data Archive for the Social Sciences, a publicly funded German data archive for secure and long-term archiving of social science data. We archived and documented tweet IDs and additional information to improve reproducibility of the initial research while also attending to ethical and legal considerations, and taking into account Twitter's terms of service in particular.

The practical and ethical challenges in acquiring and sharing digital trace data: Negotiating public-private partnerships

“…For the example of Twitter data, researchers would have to assess if they (or somebody from their team or group of collaborators) have the necessary skills to collect the data through the API or if they have sufficient funds for buying data from a reseller. If the answer to both of these questions is “no,” researchers could investigate whether they could use data from publicly available archived Twitter data from collections like TweetsKB (Fafalios et al, 2018), the Tweet ID Datasets from Documenting the Now (see https://www.docnow.io/catalog/) or large datasets stored in data archives (see, for example, Kinder-Kurlanda et al, 2017).…”

Saving social media data: Understanding data management practices among social media researchers and their implications for archives

“…Examples of other institutions, wrestling with the issues we raise, include GESIS, the Library of Congress, George Washington Libraries, the US National Archives, the UK Data Service, and the Documenting the Now Project, at a minimum. Researchers using data from social media platforms and practitioners developing archiving and dissemination services have raised issues about the scale and structure of data social media generate (Bruns & Weller, 2016;Zimmer, 2015), technical challenges in collecting data (Driscoll & Walker, 2014;Littman et al, 2018;Weller & Kinder-Kurlanda, 2015), ephemerality of social media data (Bruns & Weller, 2016;Littman et al, 2018;Weller & Kinder-Kurlanda, 2015;Zubiaga, 2018), platform application programming interface (API) restrictions (Bruns, 2019;Bruns & Weller, 2016;Kinder-Kurlanda, Weller, Zenk-Möltgen, Pfeffer, & Morstatter, 2017;Littman et al, 2018;Thomson & Kilbride, 2015;Weller & Kinder-Kurlanda, 2015), challenges for documenting the provenance of social media data (Driscoll & Walker, 2014;Weller & Kinder-Kurlanda, 2015), and privacy concerns and the ethics around preserving and disseminating social media data (Fiesler & Proferes, 2018;Thomson & Kilbride, 2015;Wheeler, 2018;Zimmer, 2015). However, the relationship between these issues and researchers' data management practices needs further analysis to guide the development of effective approaches to preservation and reuse of social media data.…”

Empfehlungen zum Umgang mit Forschungsdaten in der Kommunikationswissenschaft – AG Forschungsdaten im Auftrag des Vorstands der DGPuK

“…Diese Einschränkung betrifft sowohl Daten, die über Application Programming Interfaces (APIs) gewonnen wurden, als auch den Kauf von Daten über Dienstleister oder Daten aus direkten Forschungskooperationen mit den Plattformen. Eine umfassende Diskussion der Herausforderungen beim Teilen von Social-Media-Daten kann das Invited Paper vorliegende Dokument nicht leisten, es gibt aber bereits einige Publikationen mit Beispielen und Empfehlungen hierzu (Bishop & Gray, 2017;Kinder-Kurlanda et al, 2017;Mannheimer & Hull, 2017;Thomson, 2016;.…”