Identity and User Behavior in Online Communities

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dc.contributor.authorGuo, Cheng
dc.date.accessioned2023-03-17T22:49:00Z
dc.date.available2023-03-17T22:49:00Z
dc.date.issued2020
dc.description.abstractIn online communities, people share and discuss information at all levels of topic sensitivity. Identity policies within these communities range from real names to anonymity. The amount of user engagement, the quality of the information, disinformation behavior (e.g., trolling) may differ under different types of identity, which is currently unclear. Most of these online communities have a mechanism of content moderation. The relationship between identity and moderation is also unclear. Finally, yet little is known about how and why people make decisions of self-disclosure in online communities. My dissertation research aims to deepen our understanding of identity and user behavior in online communities. My research will benefit privacy researchers, online social network designers, policymakers, and researchers in the field of Human-Computer Interaction who study online identity and social media.en
dc.identifier.doi10.1145/3323994.3371018
dc.identifier.urihttps://dl.eusset.eu/handle/20.500.12015/4610
dc.language.isoen
dc.publisherAssociation for Computing Machinery
dc.relation.ispartofCompanion Proceedings of the 2020 ACM International Conference on Supporting Group Work
dc.subjectonline identity
dc.subjectanonymity
dc.subjectonline communities
dc.subjectinformation quality
dc.subjectmoderation
dc.subjectprivacy
dc.subjecttrolling
dc.titleIdentity and User Behavior in Online Communitiesen
dc.typeText/Conference Paper
gi.citation.startPage35–38
gi.citations.count2
gi.citations.elementSena A. Kojah, Ben Zefeng Zhang, Carolina Are, Daniel Delmonaco, Oliver L. Haimson (2025): "Dialing it Back:" Shadowbanning, Invisible Digital Labor, and how Marginalized Content Creators Attempt to Mitigate the Impacts of Opaque Platform Governance, In: Proceedings of the ACM on Human-Computer Interaction 1(9), doi:10.1145/3701191
gi.citations.elementXiaohan Ding, Buse Carik, Uma Sushmitha Gunturi, Valerie Reyna, Eugenia Ha Rim Rho (2024): Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Language, In: Proceedings of the CHI Conference on Human Factors in Computing Systems, doi:10.1145/3613904.3642117
gi.conference.locationSanibel Island, Florida, USA

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