Islamic State's Terrorist Attacks Disengage Their Supporters

Robust Evidence from Twitter

Datos Bibliográficos

ID6228484
AutoresJoan Barceló (0000-0001-6965-4342, New York University Abu Dhabi, autor de correspondencia), Elena Labzina (Microsoft (Switzerland))
Año2022
Volumen52
Número3
Páginas1490-1501
Fecha de publicación2022-07-01
Open AccessSí
TipoARTICLE
RevistaBritish Journal of Political Science (JOURNAL)
Identificadores de la revistaISSN: 0007-1234 • E-ISSN: 1469-2112
EditorialCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s0007123421000582
OpenAlexW4210495974
IdiomaEN
Citas recibidas1
Referencias citadas19

This article responds to Hansen's (2022) comment on the use of social media data to evaluate the effects of terrorist attacks on related online behavior. Hansen casts doubts on our previous finding that terrorist attacks disengage supporters of terrorist groups. The author speculates that this result might not hold when considering the bias introduced by the timing of Twitter account suspensions. We contend that this critique is deficient in several respects. First, Hansen speculates about a possible bias, yet no empirical evidence is offered to support this claim. Second, the author largely ignores our discussion of the role of Twitter account suspensions and our measures of Twitter suspension efforts and Anonymous reporting activity to alleviate this concern. In this article, rather than engaging in a qualitative debate on the amount of bias, we make two contributions. First, we offer an empirical investigation of the fragility of our previous finding to the presence of omitted variable bias. Once we account for Twitter suspension activities, we find that an extreme, unlikely amount of confounding is required to alter the estimated effect of terrorist attacks on disengagement. Second, we employ sequential g-estimation to calculate the average controlled direct effect of terrorist attacks on disengagement after controlling for two intermediate confounders: Twitter suspension behavior and Anonymous reporting activities. The estimated average controlled direct effect indicates that Islamic State's terrorist attacks significantly reduced followers in Islamic State-related Twitter accounts after de-mediating this effect from Twitter suspension efforts and Anonymous reporting activities. Further, we show that this average controlled direct effect is robust to a massive, and implausible, violation of the sequential unconfoundedness assumption. Overall, these analyses show that the timing of Twitter account suspensions, as well as any other confounder, is extremely unlikely to alter our conclusion: Islamic State's terrorist attacks disengage their supporters. We conclude this article by offering guidance on how to address practical challenges in political science research using social media data

Criminology · Disengagement theory · Empirical evidence · Islam · Political science · Social media · State (computer science · Suspension (topology · Terrorism · Computer Science · Electoral Systems and Political Participation · History · Law · Media Influence and Politics · Psychology · Social Psychology · Terrorism, Counterterrorism, and Political Violence

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