D. Kotsakos, Panos Sakkos, I. Katakis, D. Gunopulos
{"title":"#tag:迷因还是事件?","authors":"D. Kotsakos, Panos Sakkos, I. Katakis, D. Gunopulos","doi":"10.1109/ASONAM.2014.6921615","DOIUrl":null,"url":null,"abstract":"Users in social networks use hashtags for various reasons, some of them being serving search purposes, gaining attention or popularity or starting new conversation - thus, creating viral memes. In this paper we address the problem of classifying these hashtags in different categories, based on whether they represent a real life event or a social network generated meme. We compute a set of language-agnostic features to aid the classification of hashtags into events and memes and we provide an extensive study of the behavior that characterizes memes and events. We focus on Twitter social network, we apply our methods on a big dataset and reveal interesting characteristics of the two classes of hashtags.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"#tag: Meme or event?\",\"authors\":\"D. Kotsakos, Panos Sakkos, I. Katakis, D. Gunopulos\",\"doi\":\"10.1109/ASONAM.2014.6921615\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Users in social networks use hashtags for various reasons, some of them being serving search purposes, gaining attention or popularity or starting new conversation - thus, creating viral memes. In this paper we address the problem of classifying these hashtags in different categories, based on whether they represent a real life event or a social network generated meme. We compute a set of language-agnostic features to aid the classification of hashtags into events and memes and we provide an extensive study of the behavior that characterizes memes and events. We focus on Twitter social network, we apply our methods on a big dataset and reveal interesting characteristics of the two classes of hashtags.\",\"PeriodicalId\":143584,\"journal\":{\"name\":\"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASONAM.2014.6921615\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASONAM.2014.6921615","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Users in social networks use hashtags for various reasons, some of them being serving search purposes, gaining attention or popularity or starting new conversation - thus, creating viral memes. In this paper we address the problem of classifying these hashtags in different categories, based on whether they represent a real life event or a social network generated meme. We compute a set of language-agnostic features to aid the classification of hashtags into events and memes and we provide an extensive study of the behavior that characterizes memes and events. We focus on Twitter social network, we apply our methods on a big dataset and reveal interesting characteristics of the two classes of hashtags.