Loss Aversion Online: Emotional Responses to Financial Booms and Crashes
Aryan Ramchandra Kapadia, Niharika Bhattacharjee, Mung Yao Jia, Ishq Gupta, Dong Wang, Koustuv Saha
TL;DR
The paper investigates how financial booms and crashes affect online emotional expression on Reddit, testing loss aversion in real-time, large-scale social data. Using a quasi-experimental design that combines Difference-in-Differences and Causal Impact analyses across finance-focused and non-financial subreddits, it contrasts responses around two economy-wide events with a balanced baseline. The authors find stronger, coherent negative shifts in emotional language during crashes and weaker, mixed responses during booms, with posts and especially comments showing amplified effects, consistent with loss aversion. These findings advance understanding of online mental health dynamics during financial shocks and suggest design considerations for healthier online communities.
Abstract
Financial events negatively affect emotional well-being, but large-scale studies examining their impact on online emotional expression using real-time social media data remain limited. To address this gap, we propose analyzing Reddit communities (financial and non-financial) across two case studies: a financial crash and a boom. We investigate how emotional and psycholinguistic responses differ between financial and non-financial communities, and the extent to which the type of financial event affects user behavior during the two case study periods. To examine the effect of these events on expressed language, we analyze daily sentiment, emotion, and LIWC counts using quasi-experimental methods: Difference-in-Differences (DiD) and Causal Impact analyses during a financial boom and a financial crash. Overall, we find coherent, negative shifts in emotional responses during financial crashes, but weaker, mixed responses during booms, consistent with loss aversion. By exploring emotional and psycholinguistic expressions during financial events, we identify future implications for understanding online users' mental health and building connected, healthy communities.