Journal Paper Published

Abstract

This study incorporates text mining into critical discourse analysis to give a corpus-assisted discourse study of the Congressional hearing on TikTok. Topic modeling reveals two main concerns: TikTok’s ties to the Chinese Communist Party (CCP) and its digital management practices. Co-occurrence network analysis shows Republicans prioritized political matters, whereas Democrats focused on technical and managerial issues. Manual analysis finds that Chew’s responses show the preference for denying strategies, though tactics varied by question types. This explains U.S. media’s criticism of Shouzi Chew’s uncooperative attitude and underscores the increasing intertwinement of science communication and politics in Congressional hearings.

Keywords

Blame-avoiding, Congressional hearing, corpus-assisted discourse study, critical discourse analysis, TikTok