Nora Kirkizh, Roberto Ulloa, Sebastian Stier, Jürgen Pfeffer
{"title":"Predicting political attitudes from web tracking data: a machine learning approach","authors":"Nora Kirkizh, Roberto Ulloa, Sebastian Stier, Jürgen Pfeffer","doi":"10.1080/19331681.2024.2316679","DOIUrl":null,"url":null,"abstract":"Anecdotal evidence suggests that the surge of populism and subsequent political polarization might make voters’ political preferences more detectable from digital trace data. This potential scenari...","PeriodicalId":47047,"journal":{"name":"Journal of Information Technology & Politics","volume":"14 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information Technology & Politics","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/19331681.2024.2316679","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 0
Abstract
Anecdotal evidence suggests that the surge of populism and subsequent political polarization might make voters’ political preferences more detectable from digital trace data. This potential scenari...