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Specifically, a short text clustering method is employed to detect events from tweets, then the language model representations of the detected events are expanded using another set of events obtained from news articles published simultaneously. The expanded representations of events are employed as a new initialization of the clustering method to run another iteration and consequently enhance the event detection results. The proposed framework is evaluated using two datasets: a tweet dataset with event labels and a news dataset containing news articles published during the same time interval as the tweets. Experimental results show that the proposed framework improves the event detection results in terms of <jats:italic>F<\/jats:italic>1 measure compared to the results obtained from tweets only.<\/jats:p>","DOI":"10.1017\/s1351324921000462","type":"journal-article","created":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T12:53:26Z","timestamp":1643028806000},"page":"181-200","update-policy":"http:\/\/dx.doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":12,"title":["Enhancement of Twitter event detection using news streams"],"prefix":"10.1017","volume":"29","author":[{"given":"Samaneh","family":"Karimi","sequence":"first","affiliation":[]},{"given":"Azadeh","family":"Shakery","sequence":"additional","affiliation":[]},{"given":"Rakesh M.","family":"Verma","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2022,1,24]]},"reference":[{"key":"S1351324921000462_ref18","first-page":"31","author":"Fuglede","year":"2004"},{"key":"S1351324921000462_ref4","volume-title":"Topic Detection and Tracking: Event-based Information Organization","volume":"12","author":"Allan","year":"2012"},{"key":"S1351324921000462_ref19","unstructured":"Guo, W. , Li, H. , Ji, H. and Diab, M. 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