Publications
Pierri, F., Luceri, L., Chen, E., & Ferrara E. How does Twitter account moderation work? Dynamics of account creation and suspension on Twitter during major geopolitical events. EPJ Data Sci. 12, 43 (2023). https://doi.org/10.1140/epjds/s13688-023-00420-7
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Github]
Chen, E., & Ferrara, E. (2023). Tweets in Time of Conflict: A Public Dataset Tracking the Twitter Discourse on the War between Ukraine and Russia. Proceedings of the International AAAI Conference on Web and Social Media, 17(1), 1006-1013. https://doi.org/10.1609/icwsm.v17i1.22208
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Github]
Jiang, J., Chen, E., Luceri, L., Muric, G., Pierri, F., Chang, H., & Ferrara, E. (2023). What are Your Pronouns? Examining Gender Pronoun Usage on Twitter Proceedings of the International AAAI Conference on Web and Social Media, Workshop on the Data for the Wellbeing of the Most Vulnerable. https://doi.org/10.36190/2023.02
Bisberg, A.*, Jiang, J.*, Zeng, Y., Chen, E., & Ferrara, E. The Gift That Keeps on Giving: Generosity is Contagious in Multiplayer Online Games. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2), 1-22. https://doi.org/10.1145/3555120
Chen, E.*, Jiang, J.*, Chang, H.C.H., Muric, G., & Ferrara E. (2022). Charting the Information and Misinformation Landscape to Characterize Misinfodemics on Social Media: COVID-19 Infodemiology Study at a Planetary Scale.JMIR Infodemiology,2(1). https://doi.org/10.2196/32378
Matsui A.*, Chen E.*, Wang Y. & Ferrara E. (2021). The Impact of Peer Review on the Contribution Potential of Scientific Papers. PeerJ 9:e11999 https://doi.org/10.7717/peerj.11999
Allen, O., Chen, E., Ferrara E. Pictures as a Form of Protest: A Survey and Analysis of Images Posted During the Stop Asian Hate Movement on Twitter. [Extended abstract accepted to the 7th National Workshop for REU Research in Networking and Systems (REUNS 2021)]
Rao, A., Morstatter, F., Hu, M., Chen, E., Burghardt, K., Ferrara, E. & Lerman, K. (2021). Political Partisanship and Anti-Science Attitudes in Online Discussions about Covid-19. Journal of Medical Internet Research. https://doi.org/10.2196/26692
Chen, E., Deb, A., & Ferrara, E. (2021). #Election2020: The first public twitter dataset on the 2020 US presidential election. Journal of Computational Social Science. https://doi.org/10.1007/s42001-021-00117-9 [Github]
Chen, E., Chang, H., Rao, A., Lerman, K. & Ferrara, E. (2021). COVID-19 Misinformation and the 2020 U.S. Presidential Election. Harvard Kennedy School Misinformation Review. https://doi.org/10.37016/mr-2020-57
Chang, H. C. H.*, Chen, E.*, Zhang, M.*, Muric, G.*, & Ferrara, E. (2021). Social Bots and Social Media Manipulation in 2020: The Year in Review. Arxiv. https://arxiv.org/abs/2102.08436 [Submitted as a chapter in the Handbook of Computational Social Science]
Ferrara, E., Chang, H., Chen, E., Muric, G., & Patel, J. (2020). Characterizing Social Media Manipulation in the 2020 U.S. Presidential Election. First Monday, 25(11). https://doi.org/10.5210/fm.v25i11.11431 [Accepted at ICA, 71st Annual International Communication Association Conference, Acceptance Rate: 38%]
Jiang, J., Chen, E., Yan, S., Lerman, K. & Ferrara, E. (2020). Political Polarization Drives Online Conversations About Covid-19 in the United States. Human Behavior and Emerging Technologies. doi:10.1002/hbe2.202
Chen, E., Lerman, K. & Ferrara, E. (2020). Tracking Social Media Discourse About the Covid-19 Pandemic: Development of a Public Coronavirus Twitter Data Set. JMIR Public Health Surveillance,6(2), e19273. doi:10.2196/19273 [Github]
Wang, Y., Xu, T., Wu, A., Liu, M., & Chen, E.. “Our Saving Grace” The Social Simulation Game Animal Crossing’s Restorative Power During the COVID-19 Pandemic. [Accepted to the National Communication Association Conference]
Scott, A. L., Chang, H.C.H., Phelps, A., Murphy, S. & Chen, E. When Politics and a Pandemic Collide: Comparing the Use and Abuse of the Most Popular Government and Academic COVID-19 Data Platforms on Twitter. [Submitted to the International Journal of Communication and the National Communication Association Conference]
* indicates equal contribution