Abstract

Scholarly attention has been on the politicization and polarization of public issues (McCright & Dunlap, 2011; Simon et al., 2019), and the Covid-19 is one noteworthy subject. This project focuses on the influences of politicizing Covid-19 vaccines on the political polarization in the discussion related to Hong Kong on Twitter. At this stage, this study plans to explore whether the extreme sentiment in images and texts when politicizing Covid-19 contributes to political polarization. We will collect data from Twitter API (Academic), apply deep learning using Google Vision, and the funding would help to produce quality annotated data from transfer learning. The proposed study will provide a timely analysis of the politicization and polarization of Covid-19 in Hong Kong, and contribute to the literature on political polarization, social network politics, the sociopolitical significance of images, and image-as-data. Further, this project will be our starting point to investigate the causal effect of politicizing Covid-19 and the possible mechanisms with survey experiments, which leads to theoretical and practical implications on the politicization and polarization of public issues in the post-Covid-19 era.

Principal Investigator