Fernando H. Calderon, Chun-Hao Chang, C. Argueta, Elvis Saravia, Yi-Shin Chen
{"title":"Analyzing event opinion transition through summarized emotion visualization","authors":"Fernando H. Calderon, Chun-Hao Chang, C. Argueta, Elvis Saravia, Yi-Shin Chen","doi":"10.1145/2808797.2808801","DOIUrl":null,"url":null,"abstract":"Opinionated user-generated content has been increasingly flooding the Internet since the rise of the Web 2.0. Many of this content is generated by the occurrence of different events varying in time, scale and location. In recent years there has been a growing interest in having a deeper understanding of these events and how the public reacts to them. Towards this goal there is a constant development in areas such as opinion mining. Nevertheless these methods alone are insufficient to provide a greater insight regarding several event related behaviors. In this demonstration we present a time based visualization platform for analyzing events, focusing specifically on the emotional transition generated by their occurrence, to value the impact they have over society.","PeriodicalId":371988,"journal":{"name":"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2808797.2808801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Opinionated user-generated content has been increasingly flooding the Internet since the rise of the Web 2.0. Many of this content is generated by the occurrence of different events varying in time, scale and location. In recent years there has been a growing interest in having a deeper understanding of these events and how the public reacts to them. Towards this goal there is a constant development in areas such as opinion mining. Nevertheless these methods alone are insufficient to provide a greater insight regarding several event related behaviors. In this demonstration we present a time based visualization platform for analyzing events, focusing specifically on the emotional transition generated by their occurrence, to value the impact they have over society.