ABSTRACT
CSA on racial justice issues has become more popular in recent years. With the rising number of hate crimes against Asian Americans, including the Atlanta spa shooting incident, companies must consider how to position themselves in racial conversations to fulfill their civic responsibilities and create positive social impacts. This study employed the Moral Foundation Theory (MFT) to assess companies’ CSA communication regarding #StopAsianHate and its role in promoting public engagement on Twitter. The study analyzed 1,253 tweets posted by 469 business accounts engaging in the conversation about Stop Asian Hate on Twitter to identify prevalent CSA themes, various moral values used in CSA messages, and the relationship between the use of various moral values and public engagement (i.e. likes and retweets) on Twitter. This study adds to CSA scholarship by stressing a moral stance and providing suggestions for companies to leverage moral discourse in anti-Asian racism activism on social media.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 Although different version of the theory discusses the sixth dimension, liberty/opression (e.g., Graham et al., Citation2013), here we still focus on the five classical dimensions that are most widely examined.
Additional information
Notes on contributors
Chuqing Dong
Chuqing Dong is an assistant professor at the Advertising and Public Relations Department, Michigan State University. Her research focuses on public relations, corporate social responsibility, and social media.
Wenlin Liu
Wenlin Liu is an assistant professor at the Jack J. Valenti School of Communication, University of Houston. Liu’s research focuses on social media-mediated disaster communication, multiethnic community building, and social network analysis.
Yafei Zhang
Yafei Zhang is an assistant professor in the School of Journalism and Communication at the Renmin University of China. Zhang’s research focuses on strategic communication, corporate social responsibility, big data analysis, and social network analysis.