2,233
Views
37
CrossRef citations to date
0
Altmetric
Articles

Comments and Credibility: How Critical User Comments Decrease Perceived News Article Credibility

ORCID Icon, , ORCID Icon &
Pages 783-801 | Published online: 13 Feb 2020
 

ABSTRACT

Many online user comments criticize the quality of news coverage. We conducted two experimental studies to assess the effects of such critical comments on readers’ perception of the credibility of news articles and to analyze the effectiveness of counter-measures. Findings suggest that critical user comments can reduce readers’ perceived credibility of a news article. We also demonstrate that this effect depends on whether a critical user comment receives Likes or not. Additionally, readers’ credibility perceptions can be restored when a critical comment receives a reply comment by a user that includes counter-speech. A disagreeing reply by a moderator is less effective. The findings provide important implications for research on credibility perceptions in online environments and for the effects of user-generated counter-speech and interactive moderation.

Data Availability Statement

The data supporting the analyses in this manuscript are available from the authors upon request.

Additional information

Funding

Study 1 of this research was supported by the Digital Society research program funded by the Ministry of Culture and Science of the German State of North Rhine-Westphalia.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 207.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.