Research Article

The Impact of AI News Anchor Anthropomorphism on Public Opinion Attitudes: A Social Presence Mediation Model Moderated by Topic Context

Yuran ZhangXi’an International Studies University*

* Corresponding author: [email protected]

Abstract

With the widespread deployment of AI digital anchors in mainstream news contexts, the mechanisms through which their anthropomorphic design shapes users’ public opinion attitudes warrant systematic empirical investigation. Grounded in the Stimulus-Organism-Response (SOR) theoretical framework, this study employs content analysis to quantitatively examine 1,200 user comments pertaining to AI news anchors on the Weibo platform. Appearance anthropomorphism, and behavioral anthropomorphism serve as external stimuli (S); social presence serves as the organism-level mediating variable (O); and public opinion attitude constitutes the response-level outcome variable (R). News topic type is operationalized into five categories—political/current affairs, finance/business, social/livelihood, technology/culture, and sports/entertainment—as a moderating variable. Results show that both anthropomorphism dimensions strongly predict social presence (βs > 0.43, p < .001), which fully mediates their effects on attitude (large f²s). Attitudes vary by topic, and behavioral anthropomorphism’s effect is stronger in finance/business than in political topics (B = 0.222, p = .015). These findings advance the theoretical integration of AI communication effects research and online public opinion research, and offer practical guidance for differentiated public opinion governance of AI anchors in the era of intelligent media.

Keywords: AI News Anchors; Public Opinion Formation; Anthropomorphism; Social Presence; SOR Theory
Published: June 8, 2026
DOI: 10.54254/2753-7064/2026.34175
Volume: CHR Vol.111
pp. 91-99
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References

  1. mponsah, P. N., & Atianashie, M. A. (2024). Navigating the new frontier: A comprehensive review of AI in journalism. Advances in Journalism and Communication, 12 (1), 1–17.
  2. Kim, J., Xu, K., & Merrill, K., Jr. (2022). Man vs. machine: Human responses to an AI newscaster and the role of social presence. Social Science Journal, 1–13.
  3. Jang, W., Chun, J. W., Kim, S., & Kang, Y. W. (2023). The effects of anthropomorphism on how people evaluate algorithm-written news. Digital Journalism, 11(1), 103–124.
  4. Liu, Y., & Zhao, H. (2025). Young users' adaptation and acceptance of AI news anchors: A qualitative analysis based on grounded theory. New Media and Society, (01), 372–386.
  5. Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing the human: A three-factor theory of anthropomorphism. Psychological Review, 114(4), 864–886.
  6. Deng, J. (2022). How do we feel immersed? The construction and challenges of social presence in human-machine communication. Journalism & Writing, (10), 17–28.
  7. Mori, M. (1970). The uncanny valley. Energy, 7(4), 33–35.
  8. Zhan, Y. (2024). The influence of anthropomorphic features of AI anchors on consumer trust. Journal/source information pending supplement.
  9. Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. Wiley.
  10. Lee, K. M. (2004). Presence, explicated. Communication Theory, 14(1), 27–50.
  11. Bie, J. (2024). Is AI a communicative agent? The rise of human-machine communication and the limits of transcending communication ontology. Global Media Journal, 11(03), 57–73.
  12. Graefe, A., Haim, M., Haarmann, B., & Brosius, H.-B. (2018). Readers' perception of computer-generated news: Credibility, expertise, and readability. Journalism, 19(5), 595–610.
  13. Meng, L., & Yang, B. (2023). Research on public opinion focus and sentiment regarding ChatGPT. Media, (22), 87–90.
  14. Wang, S., & Wang, L. (2025). Analysis of changes in constitutive elements of online public opinion under the perspective of generative artificial intelligence. Journalism Enthusiast, (12), 16–20.
  15. Koo, T. K., & Mae, M. Y. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163.
  16. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.
  17. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
  18. Long, Q. (2024). Effect of racial homophily on AI anthropomorphism and news anchor credibility. Journal of Education, Humanities and Social Sciences, 45, 528–538.