Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
4-1-2021 12:00 AM
End Date
9-1-2021 12:00 AM
Description
Using semantic network analysis, this paper examines how three types of Twitter influencers and the regular Twitter users frame “President Trump” in the discourses of Trade War. In addition to revealing the central words and word clusters adopted by the different categories of Twitter users, this paper also studies how central words co-evolved over time between three types of Twitter influencers and regular users by using coherency and time lag analysis. Overall, we discovered that three types of Twitter influencers all took a negative stance on illustrating the President Trump’s image, while the regular Twitter users demonstrated polarized attitudes toward it. The significant time lags between the highly co-evolved word pairs indicated complicated interactions between Twitter influencers and regular Twitter users.
Building Images of “President Trump”: Comparing Co-evolutions of the Trade War Discourse between Influencers and Regular Users on Twitter
Online
Using semantic network analysis, this paper examines how three types of Twitter influencers and the regular Twitter users frame “President Trump” in the discourses of Trade War. In addition to revealing the central words and word clusters adopted by the different categories of Twitter users, this paper also studies how central words co-evolved over time between three types of Twitter influencers and regular users by using coherency and time lag analysis. Overall, we discovered that three types of Twitter influencers all took a negative stance on illustrating the President Trump’s image, while the regular Twitter users demonstrated polarized attitudes toward it. The significant time lags between the highly co-evolved word pairs indicated complicated interactions between Twitter influencers and regular Twitter users.
https://aisel.aisnet.org/hicss-54/dsm/sna/3