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pmid: 37528134
pmc: PMC10394060
AbstractTerrorist attacks not only harm citizens but also shift their attention, which has long-lasting impacts on public opinion and government policies. Yet measuring the changes in public attention beyond media coverage has been methodologically challenging. Here we approach this problem by starting from Wikipedia’s répertoire of 5.8 million articles and a sample of 15 recent terrorist attacks. We deploy a complex exclusion procedure to identify topics and themes that consistently received a significant increase in attention due to these incidents. Examining their contents reveals a clear picture: terrorist attacks foster establishing a sharp boundary between “Us” (the target society) and “Them” (the terrorist as the enemy). In the midst of this, one seeks to construct identities of both sides. This triggers curiosity to learn more about “Them” and soul-search for a clearer understanding of “Us”. This systematic analysis of public reactions to disruptive events could help mitigate their societal consequences.
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Science, Q, R, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Article, Computer Science - Computers and Society, Physics - Data Analysis, Statistics and Probability, Computers and Society (cs.CY), Medicine, Data Analysis, Statistics and Probability (physics.data-an)
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Science, Q, R, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Article, Computer Science - Computers and Society, Physics - Data Analysis, Statistics and Probability, Computers and Society (cs.CY), Medicine, Data Analysis, Statistics and Probability (physics.data-an)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |