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微博文本的事件抽取与可视化.docx

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微博文本的事件抽取与可视化 Title:EventExtractionandVisualizationofWeiboText Abstract: WiththeincreasingpopularityofsocialmediaplatformssuchasWeibo,theamountofuser-generatedcontenthasgrownexponentially.Extractingimportanteventsfromthismassiveamountoftextdatacanprovidevaluableinsightsintopublicopinions,emergingtrends,andevenreal-timeinformation.ThispaperexploresthetaskofeventextractionfromWeibotextandvisualizestheextractedeventstogainabetterunderstandingoftheunderlyinginformation. 1.Introduction: 1.1Background: SocialmediaplatformslikeWeibohavebecomeavitalsourceofinformation,whereusersexpresstheirthoughts,sharenews,andengageindiscussionsonvarioustopics.However,thelargeamountofunstructuredtextdataposeschallengesforextractingmeaningfulevents. 1.2Objective: TheobjectiveofthispaperistodevelopasystemthatcanextractessentialeventsfromWeibotextdataandvisualizetheextractedeventsforbettercomprehensionandanalysis. 2.RelatedWork: 2.1EventExtraction: Eventextractionistheprocessofidentifyingandextractingmeaningfuleventsfromtextdata.Previousstudieshaveutilizedtechniquessuchasnaturallanguageprocessing(NLP),machinelearning,andinformationretrievaltoextracteventsfromnewsarticles,socialmedia,andothertextualsources. 2.2TextVisualization: Textvisualizationtechniqueshelptransformlargetextdataintovisualrepresentations,allowinguserstograsptheoverallpatternsandrelationshipsoftheinformation.Visualizationtechniquesincludewordclouds,topicmodeling,andnetworkdiagrams. 3.DataCollectionandPreprocessing: 3.1Dataset: Alarge-scaleWeibotextdatasetiscollected,consistingofuserposts,comments,andpublicnewsfeeds.Thedatasetcoversadiverserangeoftopics,includingnews,sports,entertainment,andsocialissues. 3.2Preprocessing: ThecollectedWeibotextdataundergoespreprocessingsteps,includingtokenization,stop-wordremoval,andnormalization.Emoticons,hashtags,andusermentionsarealsoaddressedtoensureaccurateeventextraction. 4.EventExtraction: 4.1NamedEntityRecognition(NER): NamedEntityRecognitionisemployedtoidentifyimportantentitiessuchasp