Sharing of misinformation is habitual, not just lazy or biased

Abstract

Why do people share misinformation on social media? In this research (N = 2,476), we show that the structure of online sharing built into social platforms is more important than individual deficits in critical reasoning and partisan bias-commonly cited drivers of misinformation. Due to the reward-based learning systems on social media, users form habits of sharing information that attracts others' attention. Once habits form, information sharing is automatically activated by cues on the platform without users considering response outcomes such as spreading misinformation. As a result of user habits, 30 to 40% of the false news shared in our research was due to the 15% most habitual news sharers. Suggesting that sharing of false news is part of a broader response pattern established by social media platforms, habitual users also shared information that challenged their own political beliefs. Finally, we show that sharing of false news is not an inevitable consequence of user habits: Social media sites could be restructured to build habits to share accurate information.

Keywords: Facebook; habits; misinformation; outcome insensitivity; social media.

Fig. 1.

Example of true and false headlines, which were  presented in Facebook format in Studies 1 and 2.

Fig. 2.

Study 1: Probability of sharing headlines as a function of headline veracity and habit strength. Note that habit strength was represented as a continuous variable in the analysis. Error bars reflect 95% CI.

Fig. 3.

Effect size (d) comparison among each of the predictors (Social Media Habits, Past Sharing Frequency, Political Conservatism, Critical Reflection) of sharing false news.

Fig. 4.

Study 2: Probability of sharing headlines as a function of headline veracity and habit strength. In the sharing first condition (4A), weak habit participants were 2.2 times more discerning than strong habit ones. In the judge accuracy first condition (4B), this difference reduced slightly to 1.7 times; however, the three-way interaction did not approach significance. Note that habit strength was represented as a continuous variable in the analysis. Error bars reflect 95% CI.

Fig. 5.

Study 3: Probability of sharing headlines as a function of political concordance and habit strength. In the sharing first condition (5A), weak habit participants showed 1.8 times more partisan bias than strong habit ones. In the rate politics first condition (5B), this difference reduced to 1.3 times; however, the three-way interaction did not approach significance. Note that habit strength was represented as a continuous variable in the analysis. Error bars reflect 95% CI.

Fig. 6.

Study 4: Probability of sharing headlines in training phase as a function of headline veracity and reward training condition. Error bars reflect 95% CI.

Fig. 7.

Study 4: Probability of sharing headlines after rewards ended (test trials) as a function of headline veracity and reward training condition. d indicates the effect size of discernment between true and false information sharing. Error bars reflect 95% CI.