Understanding the bi-directional message diffusion mechanism in the context of IT trends and current social issues

Abstract

Amid the skyrocketing increase in social media content, understanding the information-sharing mechanism is crucial. We analyze Twitter messages on recent public issues and IT trends to examine the network's bidirectional message diffusion patterns through incoming and outgoing ties, based on the users' retweeting and mentioning behavior toward one another. We find context-based patterns. This study shows that regarding IT trends, the use of the "like" feature significantly related to users' influence, where outgoing ties had a greater mediating influence than incoming ties. During COVID-19, users prioritized obtaining reliable information. Our findings contribute toward developing diffusion mechanisms and social media strategies.