{"title":"分析演讲文稿,预测美国总统和副总统辩论的获胜者","authors":"Ian Kaplan, Andrew Rosenberg","doi":"10.1109/SLT.2012.6424266","DOIUrl":null,"url":null,"abstract":"In this paper, we describe investigations into the speech used in American Presidential and Vice-Presidential debates. We explore possible transcript-based features that may correlate with personally appealing or politically persuasive language. We identify, with chi-squared analysis, features that correlate with success in the debates. We find that with a set of surface-level features from historical debates, we can predict the winners of presidential debates with success moderately above chance.","PeriodicalId":375378,"journal":{"name":"2012 IEEE Spoken Language Technology Workshop (SLT)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Analysis of speech transcripts to predict winners of U.S. Presidential and Vice-Presidential debates\",\"authors\":\"Ian Kaplan, Andrew Rosenberg\",\"doi\":\"10.1109/SLT.2012.6424266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we describe investigations into the speech used in American Presidential and Vice-Presidential debates. We explore possible transcript-based features that may correlate with personally appealing or politically persuasive language. We identify, with chi-squared analysis, features that correlate with success in the debates. We find that with a set of surface-level features from historical debates, we can predict the winners of presidential debates with success moderately above chance.\",\"PeriodicalId\":375378,\"journal\":{\"name\":\"2012 IEEE Spoken Language Technology Workshop (SLT)\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Spoken Language Technology Workshop (SLT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SLT.2012.6424266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Spoken Language Technology Workshop (SLT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SLT.2012.6424266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of speech transcripts to predict winners of U.S. Presidential and Vice-Presidential debates
In this paper, we describe investigations into the speech used in American Presidential and Vice-Presidential debates. We explore possible transcript-based features that may correlate with personally appealing or politically persuasive language. We identify, with chi-squared analysis, features that correlate with success in the debates. We find that with a set of surface-level features from historical debates, we can predict the winners of presidential debates with success moderately above chance.