Characterizing Online Rumoring Behavior Using Multi-Dimensional Signatures
Abstract
This study offers an in-depth analysis of four rumors that spread through Twitter after the 2013 Boston Marathon Bombings. Through qualitative and visual analysis, we describe each rumor's origins, changes over time, and relationships between different types of rumoring behavior. We identify several quantitative measures-including temporal progression, domain diversity, lexical diversity and geolocation features-that constitute a multi-dimensional signature for each rumor, and provide evidence supporting the existence of different rumor types. Ultimately these signatures enhance our understanding of how different kinds of rumors propagate online during crisis events. In constructing these signatures, this research demonstrates and documents an emerging method for deeply and recursively integrating qualitative and quantitative methods for analysis of social media trace data.
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Maddock et al. (2015) identified seven behavioural reactions to rumours: misinformation, speculation, correction, question, hedge, unrelated, or neutral/other.
“Maddock et al. (2015) looked at the origins and changes of rumours over time, which led to the identification of seven behavioural reactions to rumours: misinformation, speculation, correction, question, hedge, unrelated, or neutral/other.”
From Detection and Resolution of Rumours in Social Media (2019) · cites this paper as Maddock et al. 2015
Cites
Arousal Increases Social Transmission of Information
Berger, J. (2011) · Psychological Science · doi:10.1177/0956797611413294 · Cited by 600 · see citing works
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Detection and Resolution of Rumours in Social Media
Zubiaga, A., Aker, A., Bontcheva, K., Liakata, M., & Procter, R. (2019) · ACM Computing Surveys · doi:10.1145/3161603 · Cited by 608 · see citing works
“[Maddock et al. 2015] looked at the origins and changes of rumours over time, which led to the identification of seven behavioural reactions to rumours: misinformation, speculation, correction, question, hedge, unrelated, or neutral/other.”
BackgroundStarbird, K., Arif, A., & Wilson, T. (2019) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3359229 · Cited by 370 · see citing works
Self-citationActing the Part: Examining Information Operations Within #BlackLivesMatter Discourse
Arif, A., Stewart, L. G., & Starbird, K. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274289 · Cited by 152 · see citing works
Self-citationInfluence and Improvisation: Participatory Disinformation during the 2020 US Election
Starbird, K., DiResta, R., & DeButts, M. (2023) · Social Media + Society · doi:10.1177/20563051231177943 · Cited by 90 · see citing works
Self-citation'The Government Spies Using Our Webcams': The Language of Conspiracy Theories in Online Discussions
Samory, M., & Mitra, T. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274421 · Cited by 74 · see citing works
- Authors
- Maddock, J., Starbird, K., Al-Hassani, H. J., Sandoval, D. E., Orand, M., & Mason, R. M.
- Affiliations
- University of Washington, Seattle, WA, USA
- Venue
- Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing
- Publisher
- ACM
- Published
- 2015-02-28
- Pages
- 228-241
- Cited by
- 72
- References
- 1
- Funders
- National Science Foundation (1342252)
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