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Abstract Social media has been increasingly utilized to spread breaking news and risk communications during disasters of all magnitudes. Unfortunately, due to the unmoderated nature of social media platforms such as Twitter, rumors and misinformation are able to propagate widely. Given this, a surfeit of research has studied false rumor diffusion on Twitter, especially during natural disasters. Within this domain, studies have also focused on the misinformation control efforts from government organizations and other major agencies. A prodigious gap in research exists in studying the monitoring of misinformation on social media platforms in times of disasters and other crisis events. Such studies would offer organizations and agencies new tools and ideologies to monitor misinformation on platforms such as Twitter, and make informed decisions on whether or not to use their resources in order to debunk. In this work, we fill the research gap by developing a machine learning framework to predict the veracity of tweets that are spread during crisis events. The tweets are tracked based on the veracity of their content as either true, false, or neutral. We conduct four separate studies, and the results suggest that our framework is capable of tracking multiple cases of misinformation simultaneously, with scores exceeding 87%. In the case of tracking a single case of misinformation, our framework reaches an score of 83%. We collect and drive the algorithms with 15,952 misinformation‐related tweets from the Boston Marathon bombing (2013), Manchester Arena bombing (2017), Hurricane Harvey (2017), Hurricane Irma (2017), and the Hawaii ballistic missile false alert (2018). This article provides novel insights on how to efficiently monitor misinformation that is spread during disasters.
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Emotion and humor as misinformation antidotes
Many visible public debates over scientific issues are clouded in accusations of falsehood, which place increasing demands on citizens to distinguish fact from fiction. Yet, constraints on our ability to detect misinformation coupled with our inadvertent motivations to believe false science result in a high likelihood that we will form misperceptions. As science falsehoods are often presented with emotional appeals, we focus our perspective on the roles of emotion and humor in the formation of science attitudes, perceptions, and behaviors. Recent research sheds light on how funny science and emotions can help explain and potentially overcome our inability or lack of motivation to recognize and challenge misinformation. We identify some lessons learned from these related and growing areas of research and conclude with a brief discussion of the ethical considerations of using persuasive strategies, calling for more dialogue among members of the science communication community.
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- Award ID(s):
- 1906864
- PAR ID:
- 10231796
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 118
- Issue:
- 15
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- e2002484118
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1073/pnas.2002484118
