
معرفی
Jun Zhang serves as an Assistant Professor in the School of Journalism and Strategic Media at Middle Tennessee State University (MTSU), teaching core courses including Crisis Communication in Public Relations, Social Media Practice, and Public Relations Research at both undergraduate and graduate levels. Her academic appointments include roles in the Media and Communication M.S. program, Public Relations track, and Digital Media M.S. program.
Her educational credentials feature a PhD in Mass Communications from Syracuse University (2021), an MPA from Syracuse University (2013), and a BA from Zhejiang Gongshang University (2012).
- PhD, Mass Communications, Syracuse University (2021)
- MPA, Syracuse University (2013)
- BA, Zhejiang Gongshang University (2012)
Dr. Zhang's research examines crisis spillover dynamics in branding, legitimacy mechanisms in CSR/CSA communications, organizational adoption of AI-driven technologies, and health misinformation propagation on social platforms. Her work bridges theoretical frameworks in organizational communication with practical applications in digital media strategy, emphasizing how technological innovations reshape stakeholder engagement during crises.
Analysis of her 2020-2024 publications reveals dominant trends in AI-human communication comparisons, cross-cultural health risk perception, and crisis response efficacy. Her work consistently appears in top-tier journals like Public Relations Review and Health Communication, with increasing focus on algorithmic accountability and cross-platform misinformation patterns in recent years.
As co-director of MTSU's Social Media Insights Lab, she leads research initiatives analyzing real-time social data for strategic communication applications. Her prior industry experience includes managing Gates Foundation-funded projects at Peking University's Center for Social Media Research, where she directed social listening initiatives for global health organizations including Campaign for Tobacco-Free Kids and the International Organization for Migration.
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