Name
Title | ||
|---|---|---|
Emotion Bubbles: Emotional Composition of Online Discourse Before and After the COVID-19 Outbreak |
Abstract | ||
|---|---|---|
ABSTRACT The COVID-19 pandemic has been the single most important global agenda in the past two years. In addition to its health and economic impacts, it has affected people’s psychological states, including a rise in depression and domestic violence. We traced how the overall emotional states of individual Twitter users changed before and after the pandemic. Our data, including more than 9 million tweets posted by 9,493 users, suggest that the threat posed by the virus did not upset the emotional equilibrium of social media. In early 2020, COVID-related tweets skyrocketed in number and were filled with negative emotions; however, this emotional outburst was short-lived. We found that users who had expressed positive emotions in the pre-COVID period remained positive after the initial outbreak, while the opposite was true for those who regularly expressed negative emotions. Individuals achieved such emotional consistency by selectively focusing on emotion-reinforcing topics. The implications are discussed in light of an emotionally motivated confirmation bias, which we conceptualize as emotion bubbles that demonstrate the public’s resilience to a global health risk. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3485447.3512132 | International World Wide Web Conference |
Keywords | DocType | Citations |
COVID-19, pandemic, Twitter, emotion, resilience, topic modeling | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Assem Zhunis | 1 | 0 | 0.34 |
| Gabriel Lima | 2 | 0 | 0.34 |
| Hyeonho Song | 3 | 0 | 0.34 |
| Jiyoung Han | 4 | 0 | 0.34 |
| Meeyoung Cha | 5 | 1 | 1.70 |