Soumaya Cherichi, R. Faiz
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引用次数: 1
Leveraging Temporal Markers to Detect Event from Microblogs
Oneofthemarvelsofourtimeistheunprecedenteddevelopmentanduseoftechnologiesthatsupport socialinteraction.Socialmediatingtechnologieshaveengenderedradicallynewwaysofinformation andcommunication,particularlyduringevents;incaseofnaturaldisasterlikeearthquakestsunami andAmericanpresidentialelection.ThispaperisbasedondataobtainedfromTwitterbecauseof itspopularityandsheerdatavolume.Thiscontentcanbecombinedandprocessedtodetectevents, entitiesandpopularmoodstofeedvariousnewlarge-scaledata-analysisapplications.Onthedownside, thesecontentitemsareverynoisyandhighlyinformal,makingitdifficulttoextractsenseoutofthe stream.Takingtoaccountallthedifficulties,weproposeaneweventdetectionapproachcombining linguisticfeaturesandTwitterfeatures.Finally,wepresentoursystemthataims(1)detectnewevents, (2)torecognizetemporalmarkerspatternofanevent,(3)andtoclassifyimportanteventsaccording tothematicpertinence,authorpertinenceandtweetvolume. KEywoRDS Clustering, Event Detection, Microblogs, NLP, Patterns, Social Network Analysis, Temporal Markers, Twitter
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