The role of conformity to other users’ views regarding disinformation in social media

Researchers, journalists and politicians are concerned about the effects of online disinformation. Fake news and online disinformation were especially higlihted during the American 2016 election. Some commentators have even sug-gested that online disinformation played a deciding role in that election. A survey of Candian social media users reported that 41% of respondents have found links to current affairs stories that were “obviously false”.

Online disinformation can be defined as “false information that is purposely spread to deceive people” whereas  fake news are “news articles that are intentionally and verifiably false, and could mislead readers”.

This article investigates the effects of simply pointing out to readers a fake news. Specifically, this research examines what effect it has on individuals exposed to fake news that other users take a stand against the disinformation and identifies it as such through the comment function.

The authors conducted two experimental studies:

Study 1 investigates whether readers of disinformation, upon seeing comments from others either supporting the fake news story or opposing it by attacking the news story or the original poster, respectively, are more likely to a) have a more positive or negative attitude towards the fake news b) make comments of either support or opposition to the fake news and c) share the fake news story on social media

    • One group of participants was subjected to a fake news social media post with supportive comments from other users. The second experimental group was subjected to the same fake news social media post but this time the comments critically identified the fake news as such. The third experimental group was subjected to the same fake news social media post with comments both critically identifying the fake news as such and criticizing the poster of the fake news for spreading it.
    • The results of study 1 show that the comments and actions of other users in social media can indeed affect the reactions to, and spread of, fake news online. Users exposed to comments by others users that were critical of the fake news had lower attitudes to the fake news, and were more likely to comment critically and share the fake news themselves, than users who were exposed to comments supportive of the fake news. These findings clearly demonstrate the potential and responsibility of ordinary readers in stopping the spread and mitigating the impact of fake news and online disinformation.

 

Study 2 investigates the same behavior among respondents when they are ex- posed to other users’ comment of either support or opposition to a fake news story. However, it also compares the effect of other users’ comments identifying the news as fake with the use of an official Facebook disclaimer stating that the fake news story is disputed by independent fact checkers.

  • One group of participants was subjected to a fake news social media post with no comments or disclaimers. The second group was subjected to a fake news social media post with supportive comments from other users. The third group was subjected to a fake news social media post with comments pointing out that the news was fake. The fourth group was subjected to a fake news social media post with comments supportive of the post and with a disclaimer stating its content was disputed by fact checkers.
  • The results of study 2 indicate that a disclaimer is not as effective as other users’ comments in stopping the spread of fake news. The attitudes towards the post and intentions to share the post in the group who had seen critical comments was significantly lower than in the group that had seen supportive comments

Taken together, the two studies are intended to highlight the effects and importance of other users in preventing the spread of fake news online.

Cite: Colliander, J. (2019). “This is fake news”: Investigating the role of conformity to other users’ views when commenting on and spreading disinformation in social media. Computer in Human Behavior, 97, 202-215.