Sarim Zafar, Usman Sarwar, Z. Gilani, Junaid Qadir
{"title":"Sentiment analysis of controversial topics on Pakistan's Twitter user-base","authors":"Sarim Zafar, Usman Sarwar, Z. Gilani, Junaid Qadir","doi":"10.1145/3001913.3006644","DOIUrl":null,"url":null,"abstract":"Twitter has largely become a central online social network for arguments on various global controversial topics. Detecting and analysing such topics could prove to be beneficial in understanding the sentiments of trending topics in developing regions. In this paper, we perform a systematic sentiment study of trending controversial topics on Pakistan's Twitter user-base. From the data collected we build retweet graphs, partition graphs into communities, measure community influence, and label the communities as 'for' or 'against' per topic. To the best of our knowledge this is the first work to categorise and study sentiments attached to controversial topics in a developing region.","PeriodicalId":204042,"journal":{"name":"Proceedings of the 7th Annual Symposium on Computing for Development","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 7th Annual Symposium on Computing for Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3001913.3006644","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Twitter has largely become a central online social network for arguments on various global controversial topics. Detecting and analysing such topics could prove to be beneficial in understanding the sentiments of trending topics in developing regions. In this paper, we perform a systematic sentiment study of trending controversial topics on Pakistan's Twitter user-base. From the data collected we build retweet graphs, partition graphs into communities, measure community influence, and label the communities as 'for' or 'against' per topic. To the best of our knowledge this is the first work to categorise and study sentiments attached to controversial topics in a developing region.