Gradients of Fear and Anger in the Social Media Response to Terrorism
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Date
2019-01-08
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Research suggests that public fear and anger in wake of a terror attack can each uniquely contribute to policy attitudes and risk-avoidance behaviors. Given the importance of these negative-valanced emotions, there is value in studying how terror events can incite fear and anger at various times and locations relative to an attack. We analyze 36,259 Twitter posts authored in response to the 2016 Orlando nightclub shooting and examined how fear- and anger-related language varied with time and distance from the attack. Fear-related words sharply decreased over time, though the trend was strongest at locations near the attack, while anger-related words slightly decreased over time and increased with distance from Orlando. Comparing these results to users’ pre-attack emotional language suggested that distant users remained both angry and fearful after the shooting, while users close to the attack remained angry but quickly reduced expressions of fear to pre-attack levels.
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Data Analytics, Data Mining and Machine Learning for Social Media, Digital and Social Media, emotion, social media, terrorism, text mining
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10 pages
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Proceedings of the 52nd Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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