Outnumbered Online: The Consequences of Partisan Imbalance in Online Political Discussions

Abstract

Research on the impacts of online political discussions have focused on social media "echo chambers," but less is known about how people respond to online environments dominated by those who are politically dissimilar. We conduct a preregistered experiment using a mobile application we developed to evaluate how being outnumbered by out-partisans impacts comfort with sharing opinions as well as perceptions of the platform and its users. Our app mimics a social media platform but provides researcher control over platform features to experimentally isolate their effects and uses automated chatbots to create a dynamic newsfeed for the participant. We find that engaging on a platform dominated by out-partisans reduces comfort with sharing one's opinions and lowers evaluations of the platform and its users. These findings shed light on a relatively less explored online environment (i.e., an outnumbered setting) and highlight the utility of LLMs in social science research.

Can Generative AI improve social science?

“…Though Generative AI may never replicate the spontaneous behavior of human groups, researchers may nevertheless be able to dispatch groups of bots in online spaces to approximate such behavior. Allamong et al provide a proof of concept of such research ( 30 ). These researchers were interested in studying how social media users behave when they are surrounded by people who do not share their political views.…”