By Hyungsoo Lim, Jing Wang, and Allen Huang
Posted on: 2023-04-12
Abstract
We propose an empirical setting to discover sentiment contagion in social media. We find that, after controlling for concurrent events, sentiment contagion exists in social media. We conduct additional analyses to explore how the source and valence of exposure contents and individual heterogeneity affect the degree of sentiment contagion. We find robust evidence of sentiment contagion not only in contents under the same thread but also under different threads of the same forum. The additional analysis provides evidence of negativity bias. In terms of individual heterogeneity, we find that more experienced social media users are less sensitive to sentiments in social media. Last, we find that social media users are more likely to become inactive in the long run after being exposed to more negative contents. Managerial and practical implications are discussed.
Keywords: Sentiment contagion, Individual Heterogeneity, Negativity Bias, Social Media
Presented at the 43rd International Conference on Information Systems, Copenhagen 2022
In this webinar, Dr. Chao He demonstrates the game-changing potential of artificial intelligence and natural language processing (NLP) in empowering financial institutions to proactively identify and mitigate risks, make informed decisions, and seize opportunities ahead of the curve.
This research examines sentiment contagion in social media, revealing its influence and providing valuable insights into how exposure content and individual heterogeneity impact the contagious spread of sentiments.