Just another day on Twitter: a complete 24 hours of Twitter data

Pfeffer, Juergen and Matter, Daniel and Jaidka, Kokil and Varol, Onur and Mashhadi, Afra and Lasser, Jana and Assenmacher, Dennis and Wu, Siqi and Yang, Diyi and Brantner, Cornelia and Romero, Daniel M. and Otterbacher, Jahna and Schwemmer, Carsten and Joseph, Kenneth and Garcia, David and Morstatter, Fred (2023) Just another day on Twitter: a complete 24 hours of Twitter data. In: Seventeenth International AAAI Conference on Web and Social Media (ICWSM 2023), Limassol, Cyprus

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At the end of October 2022, Elon Musk concluded his acquisition of Twitter. In the weeks and months before that, several questions were publicly discussed that were not only of interest to the platform's future buyers, but also of high relevance to the Computational Social Science research community. For example, how many active users does the platform have? What percentage of accounts on the site are bots? And, what are the dominating topics and sub-topical spheres on the platform? In a globally coordinated effort of 80 scholars to shed light on these questions, and to offer a dataset that will equip other researchers to do the same, we have collected all 375 million tweets published within a 24-hour time period starting on September 21, 2022. To the best of our knowledge, this is the first complete 24-hour Twitter dataset that is available for the research community. With it, the present work aims to accomplish two goals. First, we seek to answer the aforementioned questions and provide descriptive metrics about Twitter that can serve as references for other researchers. Second, we create a baseline dataset for future research that can be used to study the potential impact of the platform's ownership change.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: Web and Social Media, Social media usage on mobile devices; location, human mobility, and behavior
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Center of Excellence in Data Analytics
Faculty of Engineering and Natural Sciences
Depositing User: Onur Varol
Date Deposited: 17 Sep 2023 14:55
Last Modified: 17 Sep 2023 14:55
URI: https://research.sabanciuniv.edu/id/eprint/47946

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