Can You Verifi This? Studying Uncertainty and Decision-Making About Misinformation Using Visual Analytics

Authors

  • Alireza Karduni University of North Carolina Charlotte
  • Ryan Wesslen University of North Carolina Charlotte
  • Sashank Santhanam University of North Carolina Charlotte
  • Isaac Cho University of North Carolina Charlotte
  • Svitlana Volkova Pacific Northwest National Laboratory
  • Dustin Arendt Pacific Northwest National Laboratory
  • Samira Shaikh University of North Carolina Charlotte
  • Wenwen Dou University of North Carolina Charlotte

DOI:

https://doi.org/10.1609/icwsm.v12i1.15014

Keywords:

misinformation, visual analytics, fake news, social media

Abstract

We describe a novel study of decision-making processes around misinformation on social media. Using a custom-built visual analytic system, we presented users with news content from social media accounts from a variety of news outlets, including outlets engaged in distributing misinformation. We conducted controlled experiments to study decision-making regarding the veracity of these news outlets and tested the role of confirmation bias (the tendency to ignore contradicting information) and uncertainty of information on human decision-making processes. Our findings reveal that the presence of conflicting information, presented to users in the form of cues, impacts the ability to judge the veracity of news in systematic ways. We also find that even instructing participants to explicitly disconfirm given hypotheses does not significantly impact their decision-making regarding misinformation when compared to a control condition. Our findings have the potential to inform the design of visual analytics systems so that they may be used to mitigate the effects of cognitive biases and stymie the spread of misinformation on social media.

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Published

2018-06-15

How to Cite

Karduni, A., Wesslen, R., Santhanam, S., Cho, I., Volkova, S., Arendt, D., Shaikh, S., & Dou, W. (2018). Can You Verifi This? Studying Uncertainty and Decision-Making About Misinformation Using Visual Analytics. Proceedings of the International AAAI Conference on Web and Social Media, 12(1). https://doi.org/10.1609/icwsm.v12i1.15014