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Tweet, but verify : epistemic study of information verification on Twitter
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Zubiaga, Arkaitz and Ji, Heng (2014) Tweet, but verify : epistemic study of information verification on Twitter. Social Network Analysis and Mining, Volume 4 (Number 1). Article number 63. doi:10.1007/s13278-014-0163-y
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Official URL: http://dx.doi.org/10.1007/s13278-014-0163-y
Abstract
While Twitter provides an unprecedented opportunity to learn about breaking news and current events as they happen, it often produces skepticism among users as not all the information is accurate but also hoaxes are sometimes spread. While avoiding the diffusion of hoaxes is a major concern during fast-paced events such as natural disasters, the study of how users trust and verify information from tweets in these contexts has received little attention so far. We survey users on credibility perceptions regarding witness pictures posted on Twitter related to Hurricane Sandy. By examining credibility perceptions on features suggested for information verification in the field of Epistemology, we evaluate their accuracy in determining whether pictures were real or fake compared to professional evaluations performed by experts. Our study unveils insight about tweet presentation, as well as features that users should look at when assessing the veracity of tweets in the context of fast-paced events. Some of our main findings include that while author details not readily available on Twitter feeds should be emphasized in order to facilitate verification of tweets, showing multiple tweets corroborating a fact misleads users to trusting what actually is a hoax. We contrast some of the behavioral patterns found on tweets with literature in Psychology research.
| Item Type: | Journal Article | ||||
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| Subjects: | B Philosophy. Psychology. Religion > BF Psychology P Language and Literature > P Philology. Linguistics |
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| Divisions: | Faculty of Science > Computer Science | ||||
| Library of Congress Subject Headings (LCSH): | Online social networks -- Psychological aspects, Twitter | ||||
| Journal or Publication Title: | Social Network Analysis and Mining | ||||
| Publisher: | Springer Wien | ||||
| ISSN: | 1869-5450 | ||||
| Official Date: | 25 March 2014 | ||||
| Dates: |
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| Volume: | Volume 4 | ||||
| Number: | Number 1 | ||||
| Article Number: | Article number 63 | ||||
| DOI: | 10.1007/s13278-014-0163-y | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Funder: | U.S. Army Research Laboratory (ARL), United States. Defense Advanced Research Projects Agency (DARPA), National Science Foundation (U.S.) (NSF), Rensselaer Polytechnic Institute | ||||
| Grant number: | W911NF-09-2-0053 (ARL), IIS-0953149 (NSF), FA8750-13-2-0041 (DARPA) | ||||
| Embodied As: | 1 |
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