{"title":"在标签中发现知识","authors":"Rizwan Mehmood, H. Maurer, Muhammad Tanveer Afzal","doi":"10.1109/ICET.2013.6743538","DOIUrl":null,"url":null,"abstract":"Twitter is a breed of social networks that are playing a buoyant role in today's world communication. This paper is an attempt to apply knowledge discovery process on Twitter dataset comprising hashtags along with the visual analytic techniques whose purpose is to provide information to the people in such a way so that they understand concealed knowledge in the data effortlessly and meritoriously. We further analyze tweet text and metadata associated with each tweet for identification of useful patterns like \"who talks to whom\" and \"how much\". Our research reveals the impact of visualization and hierarchical clustering technique in analyzing similar groups of users. Further we investigate different social network measures that unveil the influence of users in the particular hashtags.","PeriodicalId":215372,"journal":{"name":"2013 IEEE 9th International Conference on Emerging Technologies (ICET)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Knowledge discovery in hashtags#\",\"authors\":\"Rizwan Mehmood, H. Maurer, Muhammad Tanveer Afzal\",\"doi\":\"10.1109/ICET.2013.6743538\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Twitter is a breed of social networks that are playing a buoyant role in today's world communication. This paper is an attempt to apply knowledge discovery process on Twitter dataset comprising hashtags along with the visual analytic techniques whose purpose is to provide information to the people in such a way so that they understand concealed knowledge in the data effortlessly and meritoriously. We further analyze tweet text and metadata associated with each tweet for identification of useful patterns like \\\"who talks to whom\\\" and \\\"how much\\\". Our research reveals the impact of visualization and hierarchical clustering technique in analyzing similar groups of users. Further we investigate different social network measures that unveil the influence of users in the particular hashtags.\",\"PeriodicalId\":215372,\"journal\":{\"name\":\"2013 IEEE 9th International Conference on Emerging Technologies (ICET)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 9th International Conference on Emerging Technologies (ICET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICET.2013.6743538\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 9th International Conference on Emerging Technologies (ICET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICET.2013.6743538","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Twitter is a breed of social networks that are playing a buoyant role in today's world communication. This paper is an attempt to apply knowledge discovery process on Twitter dataset comprising hashtags along with the visual analytic techniques whose purpose is to provide information to the people in such a way so that they understand concealed knowledge in the data effortlessly and meritoriously. We further analyze tweet text and metadata associated with each tweet for identification of useful patterns like "who talks to whom" and "how much". Our research reveals the impact of visualization and hierarchical clustering technique in analyzing similar groups of users. Further we investigate different social network measures that unveil the influence of users in the particular hashtags.