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1、Chapter13ASURVEYOFOPINIONMININGANDSENTIMENTANALYSISBingLiuUniversityofIllinoisatChicagoChicago,ILliub@cs.uic.eduLeiZhangUniversityofIllinoisatChicagoChicago,ILlzhang32@gmail.comAbstractSentimentanalysisoropinionminingisthecomputationalstudyofpeo-ple’so
2、pinions,appraisals,attitudes,andemotionstowardentities,in-dividuals,issues,events,topicsandtheirattributes.Thetaskistech-nicallychallengingandpracticallyveryuseful.Forexample,businessesalwayswanttofindpublicorconsumeropinionsabouttheirproductsandservice
3、s.Potentialcustomersalsowanttoknowtheopinionsofexistingusersbeforetheyuseaserviceorpurchaseaproduct.Withtheexplosivegrowthofsocialmedia(i.e.,reviews,forumdis-cussions,blogsandsocialnetworks)ontheWeb,individualsandor-ganizationsareincreasinglyusingpubli
4、copinionsinthesemediafortheirdecisionmaking.However,findingandmonitoringopinionsitesontheWebanddistillingtheinformationcontainedinthemremainsaformidabletaskbecauseoftheproliferationofdiversesites.Eachsitetypicallycontainsahugevolumeofopinionatedtextthat
5、isnotalwayseasilydecipheredinlongforumpostingsandblogs.Theaveragehumanreaderwillhavedifficultyidentifyingrelevantsitesandaccuratelysum-marizingtheinformationandopinionscontainedinthem.Moreover,itisalsoknownthathumananalysisoftextinformationissubjecttocon
6、-siderablebiases,e.g.,peopleoftenpaygreaterattentiontoopinionsthatareconsistentwiththeirownpreferences.Peoplealsohavedifficulty,owingtotheirmentalandphysicallimitations,producingconsistentC.C.AggarwalandC.X.Zhai(eds.),MiningTextData,DOI10.1007/978-1-4614
7、-3223-4_13,415©SpringerScience+BusinessMedia,LLC2012416MININGTEXTDATAresultswhentheamountofinformationtobeprocessedislarge.Au-tomatedopinionminingandsummarizationsystemsarethusneeded,assubjectivebiasesandmentallimitationscanbeovercomewithanobjectivesen
8、timentanalysissystem.Inthepastdecade,aconsiderableamountofresearchhasbeendoneinacademia[58,76].Therearealsonumerouscommercialcompaniesthatprovideopinionminingservices.Inthischapter,wefirstdefinetheopinionminingproblem.Fromthedefinition,wew
