{"title":"学习Reddit上的用户声誉","authors":"Alexandre Parmentier, R. Cohen","doi":"10.1145/3350546.3352524","DOIUrl":null,"url":null,"abstract":"The rapid growth of online social networks and the recognition of their potency as a medium for the spread of misinformation has provoked a growing interest in modelling reputation and trust in multi agent networks. Intended as a novel approach towards modelling the effects a user is having on the well-being of an online community, this paper presents a method for extracting features from tree-shaped discussions and evaluates a large set of linguistic and metadata based features for their predictive ability in a data set of Reddit comments. We show that some qualities of discussion-starting comments are predictable based solely on an analysis of the discussion that follows, and outline a road-map for how learning associations between community reactions and detectable antisocial behaviour could be used to model the reputation of users.","PeriodicalId":171168,"journal":{"name":"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Learning User Reputation on Reddit\",\"authors\":\"Alexandre Parmentier, R. Cohen\",\"doi\":\"10.1145/3350546.3352524\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid growth of online social networks and the recognition of their potency as a medium for the spread of misinformation has provoked a growing interest in modelling reputation and trust in multi agent networks. Intended as a novel approach towards modelling the effects a user is having on the well-being of an online community, this paper presents a method for extracting features from tree-shaped discussions and evaluates a large set of linguistic and metadata based features for their predictive ability in a data set of Reddit comments. We show that some qualities of discussion-starting comments are predictable based solely on an analysis of the discussion that follows, and outline a road-map for how learning associations between community reactions and detectable antisocial behaviour could be used to model the reputation of users.\",\"PeriodicalId\":171168,\"journal\":{\"name\":\"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3350546.3352524\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3350546.3352524","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The rapid growth of online social networks and the recognition of their potency as a medium for the spread of misinformation has provoked a growing interest in modelling reputation and trust in multi agent networks. Intended as a novel approach towards modelling the effects a user is having on the well-being of an online community, this paper presents a method for extracting features from tree-shaped discussions and evaluates a large set of linguistic and metadata based features for their predictive ability in a data set of Reddit comments. We show that some qualities of discussion-starting comments are predictable based solely on an analysis of the discussion that follows, and outline a road-map for how learning associations between community reactions and detectable antisocial behaviour could be used to model the reputation of users.