{"title":"利用格兰杰因果关系量化社交媒体对 1 月 6 日美国国会大厦暴动期间暴力事件的预测。","authors":"Qinghua Li, Brayden G King, Brian Uzzi","doi":"10.1098/rsif.2024.0314","DOIUrl":null,"url":null,"abstract":"<p><p>Protests involving brute force are growing in number and are viewed as a likely source of increased collective violence in industrialized nations. Yet, our scientific understanding of how violent protests are related to a leader's social media communications during protests remains nascent. Here, we analyse new data from the 6 January 'march on the US Capitol' to quantify the links between leadership, social media and levels of violence. Using data on thousands of live footage videos, Trump's tweets and rally speech, other rally speeches and #StopTheSteal tweets, we apply Granger regression methods to analyse the links between former President Trump's tweets, #StopTheSteal tweets, rally speeches and the severity and duration of outbreaks of violence and weapons use during the riot. We find that Trump's tweets predict bursts in rioters' levels and duration of violence and weapons use. Trump's tweets also predict changes in the volume and sentiments of #StopTheSteal tweets, which in turn explain additional variance in levels of violence and weapons use over the course of the riot. Our findings reveal new patterns of behaviour that link an authority figure's online behaviour during a protest and the shift from peaceful protesting to violence.</p>","PeriodicalId":17488,"journal":{"name":"Journal of The Royal Society Interface","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11538902/pdf/","citationCount":"0","resultStr":"{\"title\":\"Quantifying social media predictors of violence during the 6 January US Capitol insurrection using Granger causality.\",\"authors\":\"Qinghua Li, Brayden G King, Brian Uzzi\",\"doi\":\"10.1098/rsif.2024.0314\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Protests involving brute force are growing in number and are viewed as a likely source of increased collective violence in industrialized nations. Yet, our scientific understanding of how violent protests are related to a leader's social media communications during protests remains nascent. Here, we analyse new data from the 6 January 'march on the US Capitol' to quantify the links between leadership, social media and levels of violence. Using data on thousands of live footage videos, Trump's tweets and rally speech, other rally speeches and #StopTheSteal tweets, we apply Granger regression methods to analyse the links between former President Trump's tweets, #StopTheSteal tweets, rally speeches and the severity and duration of outbreaks of violence and weapons use during the riot. We find that Trump's tweets predict bursts in rioters' levels and duration of violence and weapons use. Trump's tweets also predict changes in the volume and sentiments of #StopTheSteal tweets, which in turn explain additional variance in levels of violence and weapons use over the course of the riot. Our findings reveal new patterns of behaviour that link an authority figure's online behaviour during a protest and the shift from peaceful protesting to violence.</p>\",\"PeriodicalId\":17488,\"journal\":{\"name\":\"Journal of The Royal Society Interface\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11538902/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of The Royal Society Interface\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1098/rsif.2024.0314\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of The Royal Society Interface","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1098/rsif.2024.0314","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Quantifying social media predictors of violence during the 6 January US Capitol insurrection using Granger causality.
Protests involving brute force are growing in number and are viewed as a likely source of increased collective violence in industrialized nations. Yet, our scientific understanding of how violent protests are related to a leader's social media communications during protests remains nascent. Here, we analyse new data from the 6 January 'march on the US Capitol' to quantify the links between leadership, social media and levels of violence. Using data on thousands of live footage videos, Trump's tweets and rally speech, other rally speeches and #StopTheSteal tweets, we apply Granger regression methods to analyse the links between former President Trump's tweets, #StopTheSteal tweets, rally speeches and the severity and duration of outbreaks of violence and weapons use during the riot. We find that Trump's tweets predict bursts in rioters' levels and duration of violence and weapons use. Trump's tweets also predict changes in the volume and sentiments of #StopTheSteal tweets, which in turn explain additional variance in levels of violence and weapons use over the course of the riot. Our findings reveal new patterns of behaviour that link an authority figure's online behaviour during a protest and the shift from peaceful protesting to violence.
期刊介绍:
J. R. Soc. Interface welcomes articles of high quality research at the interface of the physical and life sciences. It provides a high-quality forum to publish rapidly and interact across this boundary in two main ways: J. R. Soc. Interface publishes research applying chemistry, engineering, materials science, mathematics and physics to the biological and medical sciences; it also highlights discoveries in the life sciences of relevance to the physical sciences. Both sides of the interface are considered equally and it is one of the only journals to cover this exciting new territory. J. R. Soc. Interface welcomes contributions on a diverse range of topics, including but not limited to; biocomplexity, bioengineering, bioinformatics, biomaterials, biomechanics, bionanoscience, biophysics, chemical biology, computer science (as applied to the life sciences), medical physics, synthetic biology, systems biology, theoretical biology and tissue engineering.