2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)
from 13-10-2022 to 16-10-2022
[en] COVID-19 content ; digital communication ; emotions ; politicization ; pandemic management ; social media
[en] COVID-19 content spreads wildly on social media and produces significant effects in both causing social panic and assisting pandemic management. However, what really enhances the diffusion of pandemic-related content during COVID-19, particularly from the perspective of the content itself, remains unexplored. Using large-scale COVID-19 tweets posted on Twitter, this paper empirically examines the effects of the four key characteristics, namely emotions, topics, hashtags, and mentions, on information spread in the pandemic. The empirical results show that most negative emotions have positive effects on retweeting. Nevertheless, the positive effect of trust on retweeting is unexpectedly the strongest. And the positive effects of the political topics and mentioning politicians further indicate that people are sensitive to the politicization of information during the pandemic. The strongest anger intensity in the political topic also needs to be noticed. The results complement the extant understanding of information diffusion during COVID-19 and provide insights for the governments to understand the psychology and behavior of large population during disasters like global pandemics.
NSFC
Researchers ; Professionals ; Students ; General public
[University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > IRiSC >]
