Speaker: Charlotte Lambert
Title: Moderator Perspectives on Encouraging Desirable Behavior
Abstract: Online moderation is often characterized as solely punitive, however, moderators can not only reactively punish bad actors but also proactively create norms and support the values they want to see within their communities. Positive reinforcement, a principle of behavioral psychology, is a strategy for encouraging desired behaviors through rewards and has been shown to be effective in offline contexts. Given this background, this talk explores my work in understanding whether positive reinforcement has a role in online moderation through a survey of Reddit moderators. I will present two taxonomies constructed from the survey responses to better understand what moderators find desirable in their communities and the actions they take to reward those behaviors. Through this research, we motivate the need to understand the efficacy of positive reinforcement as a moderation strategy and propose design solutions to enable its adoption by more moderators.
Bio: Charlotte Lambert is a 5th year Ph.D. candidate advised by Eshwar Chandrasekharan studying problems in social computing. In particular, her work advocates for wider adoption of positive, proactive forms of moderation in online spaces to complement punitive techniques and support online community health. She has presented her work at ICWSM and will soon present at CSCW 2024. Charlotte is a previous recipient of the Saburo Muroga Endowed Fellowship and the C. W. Gear Outstanding Graduate Student Award.
Speaker: Jackie Chan
Title: Examining Algorithmic Curation on Social Media Platforms
Abstract: Given the immense amount of social media data that is being produced daily, social media platforms have increasingly relied on algorithms to filter, rank, and organize the content being presented in a process known as algorithmic curation. Despite the prevalence of algorithmic curation, platforms are naturally opaque regarding how these proprietary systems work, making it more challenging to study these systems. In this talk, I will discuss my thesis on algorithmic citation systems on social media. More specifically, my studies on Reddit’s trending feed and how it impacts the users, posts, and online communities that appear on it. By grappling with how these algorithms integrate into our digital lives, we can better understand their impacts and inform better design practices and content moderation strategies.
Bio: Jackie Chan is a 5th year Ph.D. candidate studying algorithmically-curated feeds on social media with Dr. Eshwar Chandrasekharan. Currently, he studies how trending feeds impact users and online communities on Reddit. Jackie is also an NSF Fellow Honorable Mention and has presented his work at ICWSM. Before coming to Illinois, he earned his bachelor’s degree in computer science and mathematics from Carleton College in his home state of Minnesota.