Pooja JainM. TechNeetu VermaB PangP TurneyJ RiloffLoren TerveenMinqing HuBing LiuTetsuya NasukawaJeonghee YiDaveWiebejanyceWiebejanyceHatzivassiloglouJunichi TatemuraS MorinagaP TurneyMichael L LittmanA EsuliF &sebastianiSmeureanu IonBucur CristianM NileshShelkeVilas ShriniwasdeshpandeThakre
In recent years, the remarkableexpansion of web technologies, lead to an massive quantity of user generated information in online systems.This large amount of information on web platforms make them viable for use as data sources, in applications based on opinion mining and sentiment analysis.Sentiment analysishas become a vital part in today's era.Post massiveexpansion of web technology, reviews existing on net are in surplus quantity.It wouldbe more helpful to an individual or organization if these opinions serve accurate sentiment of the whole review/document.This paper implements naïve Bayes algorithm to categorize the sentence in positive, negative and neutral precisely.So,weexecuted the proposed technique and we evaluated its performance, and suggested instructions of enhancement.
Arga Aditia PurnamaYoannes Romando Sipayung
Suraj GowdaB. R. ArchanaPraajna ShettigarKislay Kumar Satyarthi
Ruth AtubonengiV.I.E AnirehDaniel Matthias
Arif Abdurrahman FarisiYuliant SibaroniSaid Al Faraby
Zhurwahayati PutriSugiyarto SugiyartoSalafudin Salafudin