DEPICTING U.S.-CHINA DISPUTES ON TECH GIANTS THROUGH SOCIAL MEDIA: AN ATTEMPT OF COMPUTATIONAL POLITICAL COMMUNICATION

Abstract

Computational political communication based on big data analytics of social media texts brings a prospecting framework to understand the public's perception of and interaction with political issues globally. This study collects a large scale of user-generated Twitter data to delineate online political communication dynamics upon U.S.-China disputes. Tech giants Huawei, Tencent, and ByteDance are chosen as epitomes of the U.S.-China power game to grasp more detailed opinions. Seven English-speaking countries: the U.S., the U.K., Canada, Australia, New Zealand, India, and Pakistan, are selected as keywords for filtering among tweets collected from March 2020 to March 2021 across the globe. Automated text-based sentiment analysis is conducted. This study shows that the popularity of discussions about given countries and companies is inconsistent and might be event-induced. Also, the discourse of all these companies is interrelated rather than separated. This research facilitates future studies on fine-grained, categorized, and automated sentiment & discourse analysis to depict a broader panorama of online public opinion.