In the 2019/2020 academic year, around 370,000 Chinese students studied at U.S. colleges and universities. During the COVID-19 pandemic, social media serve as an important channel for in-U.S. Chinese college students to learn about the pandemic-related news and information in both China and the United States. However, due to the wide circulation of misinformation on social media and the censored Chinese media system, the question remains whether in-U.S. Chinese students trust the social media platforms and information sources they depend on. This thesis seeks to answer this question by drawing upon the literature about media credibility and the Media System Dependency theory. Specifically, the study examines whether in-U.S. Chinese college students’ media dependency level can positively predict their perceived credibility level of different social media platforms and information sources within the platforms when consuming news related to COVID-19. Based on an online survey, this thesis found that in-U.S. Chinese students still depended mostly on WeChat, a Chinese social media platform, and perceived it most credible for consuming both Chinese and U.S. COVID-19 information. Despite their experience staying in the U.S., the Chinese students also largely depended on and trusted Chinese governmental and mainstream news media sources within the social media. In addition, media dependency levels could positively predict the perceived credibility level of all social media platforms and information sources. That is, in-U.S. Chinese students tend to trust the media and information sources they depend on. Theoretically, this thesis extends the previous literature about media dependency and credibility to social media and public health crisis contexts, further considering the different features and affordances of various social media platforms.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/42615 |
| Date | 17 May 2021 |
| Creators | Liu, Siyu |
| Contributors | Guo, Lei, Wells, Chris |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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