Extracting Criminal-Related Events from Arabic Tweets: A Spatio-Temporal Approach

Recently,Twitterasoneofsocialnetworkshasbeenconsideredasarichsourceofspatio-temporal informationandsignificantrevenueforminingdata.Eventdetectionfromtweetscanhelptopredict moreseriousreal-worldevents.Suchas:criminalevents,naturalhazards,andthespreadofepidemics. Etc.Thispaperdealswithevent-basedextractionforcriminalincidentsfromArabictweets.Itpresents aframeworkthatsupportsautomatedextractionofspatialandtemporalinformationfromtweets. Theproposedapproachisbasedoncombiningvarious indicators, includingthenamesofplaces andtemporalexpressionsthatappearinthetweetmessage,relatedtweetingtime,andadditional locationsfromtheuser’sprofile.Theeffectivenessofthesystemwasevaluatedintermofrecall, precisionandf-measure. KEywoRdS Arabic Language Processing, Gazetteers, Information Extraction, Processing Tweets, Spatiotemporal Information

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