{"title":"推特愤怒预测2016年美国总统大选的县级结果","authors":"K. Bernecker, Michael Wenzler, K. Sassenberg","doi":"10.5334/IRSP.256","DOIUrl":null,"url":null,"abstract":"In the aftermath of the 2016 United States presidential election, experts and journalists speculated that angry voters had supported the unexpected winner Donald Trump. The present study used a sample of 148 million tweets posted by U.S. citizens from across 1,347 counties, classified with regard to emotional content, to predict the election results at county level. As expected, Donald Trump received more support in counties where people tweeted more anger and negative emotions, even when various county characteristics and conservative vote choice in the preceding presidential election were controlled. These findings might be an outcome of emotional resonance—voters being attracted by political appeals that match their emotions—because Trump used more anger and negative emotion words in his campaign than the other presidential candidates in 2012 and 2016. The findings suggest that negative emotions played a critical role in the 2016 presidential election.","PeriodicalId":45461,"journal":{"name":"International Review of Social Psychology","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Tweeted Anger Predicts County-Level Results of the 2016 United States Presidential Election\",\"authors\":\"K. Bernecker, Michael Wenzler, K. Sassenberg\",\"doi\":\"10.5334/IRSP.256\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the aftermath of the 2016 United States presidential election, experts and journalists speculated that angry voters had supported the unexpected winner Donald Trump. The present study used a sample of 148 million tweets posted by U.S. citizens from across 1,347 counties, classified with regard to emotional content, to predict the election results at county level. As expected, Donald Trump received more support in counties where people tweeted more anger and negative emotions, even when various county characteristics and conservative vote choice in the preceding presidential election were controlled. These findings might be an outcome of emotional resonance—voters being attracted by political appeals that match their emotions—because Trump used more anger and negative emotion words in his campaign than the other presidential candidates in 2012 and 2016. The findings suggest that negative emotions played a critical role in the 2016 presidential election.\",\"PeriodicalId\":45461,\"journal\":{\"name\":\"International Review of Social Psychology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2019-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Review of Social Psychology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.5334/IRSP.256\",\"RegionNum\":4,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PSYCHOLOGY, SOCIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Social Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.5334/IRSP.256","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PSYCHOLOGY, SOCIAL","Score":null,"Total":0}
Tweeted Anger Predicts County-Level Results of the 2016 United States Presidential Election
In the aftermath of the 2016 United States presidential election, experts and journalists speculated that angry voters had supported the unexpected winner Donald Trump. The present study used a sample of 148 million tweets posted by U.S. citizens from across 1,347 counties, classified with regard to emotional content, to predict the election results at county level. As expected, Donald Trump received more support in counties where people tweeted more anger and negative emotions, even when various county characteristics and conservative vote choice in the preceding presidential election were controlled. These findings might be an outcome of emotional resonance—voters being attracted by political appeals that match their emotions—because Trump used more anger and negative emotion words in his campaign than the other presidential candidates in 2012 and 2016. The findings suggest that negative emotions played a critical role in the 2016 presidential election.
期刊介绍:
The International Review of Social Psychology (IRSP) is supported by the Association pour la Diffusion de la Recherche Internationale en Psychologie Sociale (A.D.R.I.P.S.). The International Review of Social Psychology publishes empirical research and theoretical notes in all areas of social psychology. Articles are written preferably in English but can also be written in French. The journal was created to reflect research advances in a field where theoretical and fundamental questions inevitably convey social significance and implications. It emphasizes scientific quality of its publications in every area of social psychology. Any kind of research can be considered, as long as the results significantly enhance the understanding of a general social psychological phenomenon and the methodology is appropriate.