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February 11, 20260 citations

How Do Negative Online Comments Deter Potential Fans? A Study on the Impact of Anti-Fan Behaviour on Celebrity Image and Feasible Strategies

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RGRan Gao

Key Points

  • The research aims to investigate how negative online comments impact celebrity image and hinder potential fans.
  • Examined celebrity image and public opinion dynamics through case study of Roy Wang.
  • Analyzed the influence of online negative comments on public perceptions.
  • Applied theories of spiral of silence and third-person effect to frame the analysis.
  • Negative comments significantly damage celebrity image and hinder the growth of their fan base.
  • Ordinary users' perceptions of celebrities shift negatively due to online criticism.
  • Proposed strategies aim to mitigate the harmful effects of malicious comments on public relations.

Abstract

The image of celebrities is highly dependent on online public opinion. However, some haters are easily driven by personal emotions, herd mentality and other factors to spread malicious comments and other irrational behaviours on the Internet, causing the spread of negative public opinion. A passer-by on the Internet refers to an ordinary Internet user who has no direct interest or preconceived position in a specific online community. Online bad reviews can not only affect a celebrity’s image, public relations and fan base, but also affect passers-by’s perception or evaluation of the celebrity, thereby hindering them from turning into actual followers. Combining the theory of the spiral of silence and the third-person effect, this paper explores how the remarks of haters shape public perception. Using Roy Wang’s social media feedback as a case study, this paper systematically analyses the impact of online bad reviews on the image of ordinary people and celebrities. In response to this issue, several implications have been proposed, and it is expected that these strategies will reduce the impact of bad reviews on the public relations image of celebrities and lower the probability of passers-by being misled by a large number of bad reviews.

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Cite This Study

Ran Gao (2026) studied this question.

synapsesocial.com/papers/698c1c8e267fb587c655f027https://doi.org/10.1051/shsconf/202622803006/pdf
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