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. 2024 Nov 3;14(1):26525.
doi: 10.1038/s41598-024-77350-5.

The emotional effect of terrorism

Vincenzo Bove #  1 , Georgios Efthyvoulou #  2 , Armine Ghazaryan #  3 , Harry Pickard #  4
Affiliations

The emotional effect of terrorism

Vincenzo Bove et al. Sci Rep. .

Abstract

Terrorism causes emotional reactions among public audiences, with downstream consequences for their well-being, attitudes and policy preferences. We utilise a novel approach which harnesses a unique dataset of Twitter activity from 324K users to precisely capture emotional responses to terrorism. Our results demonstrate that terrorist attacks induce dramatic spikes in various discrete emotions of a negative valence, which vary based on the characteristics of the attacks. Furthermore, we show that the terrorism-induced effects on emotions are accompanied by changes in feelings about immigration.

Keywords: Emotions; Sentiments; Terrorism; Twitter.

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Figures

Fig. 1
Fig. 1
The emotional effect of terrorism: time-to-event analysis. Notes: The figure shows the evolution of negative feelings 24 hours before and 24 hours after the sampled attacks. The tweets are aggregated at the hour level. The blue (red) solid line shows the 3-hour moving average estimates before (after) the attacks, taking the hour before the attack as the baseline. The tweets posted in the hour after the attack are dropped from the estimations. The shaded areas show the 95 percent confidence intervals.
Fig. 2
Fig. 2
The emotional effect of terrorism: heterogeneity analysis. Notes: The figure shows the post-attack estimates for the 24-hour bandwidth (based on the specification in panel B of Table 1) when we run separate regressions for the attack groups displayed on the vertical axis. The horizontal lines signify the 95% confidence intervals of the corresponding estimates.
Fig. 3
Fig. 3
The emotional content of immigration-related tweets. Notes: This figure shows the pre- and post-attack average values of the negative sentiment and emotions about immigration. The analysis is based on tweets that include the word ‘immigration’ and other related terms, as identified using a Word2Vec algorithm; i.e., migrant, deport, illegals, undocumented, refugee, citizenship, visa, illegal alien, expedited removal, asylum seeker, as well as typos of the word ‘immigration’. Black bars denote the standard error of the mean.
See this image and copyright information in PMC

References

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