{"title":"Opinion Influence Analysis in Online Forum Threads","authors":"Dumitru-Clementin Cercel, Stefan Trausan-Matu","doi":"10.1109/SYNASC.2014.38","DOIUrl":null,"url":null,"abstract":"This paper treats the phenomenon of opinion influence in online forum threads. Influence among users' opinions is analyzed by taking into consideration the changes in their opinions. Therefore, a change in a user's opinion is modeled as a change of his/her posts' polarity. The hypothesis that underlies our research is that users' opinions may change over time as a consequence of the interactions between them in online discussions such as online forum threads. Moreover, a user's new post in an online forum thread is considered to have an influence on all the posts sent by other users in reaction to this. Our approach to the opinion influence phenomenon that arises in online forum threads is based on Natural Language Processing techniques, Latent Semantic Analysis and Post-Level Sentiment Analysis. The results obtained by us show that all the previous posts that contain opinions have an influence, more or less significant, on a new post in the same online forum thread.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2014.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper treats the phenomenon of opinion influence in online forum threads. Influence among users' opinions is analyzed by taking into consideration the changes in their opinions. Therefore, a change in a user's opinion is modeled as a change of his/her posts' polarity. The hypothesis that underlies our research is that users' opinions may change over time as a consequence of the interactions between them in online discussions such as online forum threads. Moreover, a user's new post in an online forum thread is considered to have an influence on all the posts sent by other users in reaction to this. Our approach to the opinion influence phenomenon that arises in online forum threads is based on Natural Language Processing techniques, Latent Semantic Analysis and Post-Level Sentiment Analysis. The results obtained by us show that all the previous posts that contain opinions have an influence, more or less significant, on a new post in the same online forum thread.
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