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However, due to the exponentially increasing number of users on Twitter platform, the volume of content generated is tremendously high. In this paper we address the information overload problem of the Twitter and present a framework for event detection with hierarchical visualization specifically for sports events. We propose a novel Event Tree algorithm which detects and generates a hierarchy of events through recursive hierarchical clustering. The different levels of the hierarchy represent the events at different granularities of time and thus offer dual advantages. Firstly, it takes care of the users with varied level of interest in the particular sports event. Secondly, the users may get finer details for specific segments of the sport holdings as per their appeal. We test and report results of our framework for the Indian Premier League Twenty20 2016 season cricket match dataset.<\/jats:p>","DOI":"10.3233\/jifs-169238","type":"journal-article","created":{"date-parts":[[2017,3,31]],"date-time":"2017-03-31T18:22:06Z","timestamp":1490984526000},"page":"2953-2961","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Hierarchical visualization of sport events using Twitter"],"prefix":"10.1177","volume":"32","author":[{"given":"Nadeem","family":"Akhtar","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh, UP, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bushra","family":"Siddique","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh, UP, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2017,3,29]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1109\/ASONAM.2011.74","article-title":"A novel approach for event detection by mining spatio-temporal information on microblogs","author":"Lee C.H.","year":"2011","unstructured":"LeeC.H., YangH.C., ChienT.F. and WenW.S., A novel approach for event detection by mining spatio-temporal information on microblogs, Proc - 2011 Int Conf Adv Soc Networks Anal Mining, ASONAM2011, 2011, pp. 254\u2013259.","journal-title":"Proc - 2011 Int Conf Adv Soc Networks Anal Mining"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772777"},{"key":"e_1_3_1_4_2","first-page":"192","article-title":"Predicting the political alignment of twitter users","author":"Conover M.D.","year":"2011","unstructured":"ConoverM.D., Gon\u00e7alvesB., RatkiewiczJ., FlamminiA. and MenczerF., Predicting the political alignment of twitter users, Proc - 2011 IEEE Int Conf Privacy, Secur Risk Trust IEEE Int Conf Soc Comput PASSAT\/SocialCom 2011, 2011, pp. 192\u2013199.","journal-title":"Proc - 2011 IEEE Int Conf Privacy, Secur Risk Trust IEEE Int Conf Soc Comput PASSAT\/SocialCom 2011"},{"key":"e_1_3_1_5_2","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1145\/1150402.1150476","article-title":"Structure and evolution of online social networks","author":"Kumar R.","year":"2006","unstructured":"KumarR., NovakJ. and TomkinsA., Structure and evolution of online social networks, Proc 12th ACM SIGKDD Int Conf Knowl Discov Data Min - KDD \u201906, 2006, p. 611.","journal-title":"Proc 12th ACM SIGKDD Int Conf Knowl Discov Data Min - KDD \u201906"},{"key":"e_1_3_1_6_2","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1145\/1401890.1401948","article-title":"Microscopic evolution of social networks","author":"Leskovec J.","year":"2008","unstructured":"LeskovecJ., BackstromL., KumarR. and TomkinsA., Microscopic evolution of social networks, Proc 14th ACM SIGKDD Int Conf Knowl Discov Data Min, 2008, pp. 462\u2013470.","journal-title":"Proc 14th ACM SIGKDD Int Conf Knowl Discov Data Min"},{"key":"e_1_3_1_7_2","unstructured":"KermanM.C. 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