Literature DB >> 32512901

Space-Time Surveillance of Negative Emotions After Consecutive Terrorist Attacks in London.

Dajun Dai1, Ruixue Wang1,2.   

Abstract

Terrorist attacks pose significant threats to mental health. There is dearth information about the impact of consecutive terrorist attacks on space-time concentrations of emotional reactions. This study collected (1) Twitter data following the two terrorist attacks in London in March and June of 2017, respectively, and (2) deprivation data at small areal levels in the United Kingdom. The space-time permutation model was used to detect the significant clusters of negative emotions, including fear, sadness, and anger in tweets. Logistic regression models were used to examine the social deprivation of communities associated with negative tweeting. The results reported two significant clusters after the March attack, one was in London, ten days after the attack, and the other was far from the attack site between Manchester and Birmingham, three days after the attack. Attention to the reoccurring attack in June diminished quickly. The socially deprived communities experienced double disadvantage-sending fewer tweets but expressing more negative emotions than their counterparts. The findings suggest that terrorism can affect public emotions far and broad. There is a potential for surveillance to rapidly identify geographically concentrated emotions after consecutive or prolonged disasters using social media data.

Entities:  

Keywords:  GIS; Twitter; disaster; social media; terrorist attack

Year:  2020        PMID: 32512901     DOI: 10.3390/ijerph17114000

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


  3 in total

1.  Crowd Detection in Mass Gatherings Based on Social Media Data: A Case Study of the 2014 Shanghai New Year's Eve Stampede.

Authors:  Jiexiong Duan; Weixin Zhai; Chengqi Cheng
Journal:  Int J Environ Res Public Health       Date:  2020-11-20       Impact factor: 3.390

2.  Exploring spatiotemporal changes in the multi-granularity emotions of people in the city: a case study of Nanchang, China.

Authors:  Xin Xiao; Chaoyang Fang; Hui Lin; Li Liu; Ya Tian; Qinghua He
Journal:  Comput Urban Sci       Date:  2022-01-04

3.  Space-Time Dependence of Emotions on Twitter after a Natural Disaster.

Authors:  Sonja I Garske; Suzanne Elayan; Martin Sykora; Tamar Edry; Linus B Grabenhenrich; Sandro Galea; Sarah R Lowe; Oliver Gruebner
Journal:  Int J Environ Res Public Health       Date:  2021-05-16       Impact factor: 3.390

  3 in total

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