SENTIMENT ANALYSIS IN SOCIAL MEDIA ON FACEBOOK

Abstract

In ithis iadvanced istage itechnology iwhere igiving i& idevouring imanagements ithrough ionline itrade ihas iturned iinto iday ito iday iactivities i(task), ieverybody iwants ito itake ian iinterest iand igive isuppositions iabout ithe iadministrations ihe/she ispends. ithese idays iare ioccurring isubstantially imore ion isocial iareas ias iopposed ito iin ia ifeedback ibox. iFacebook iis ia istandout iamongst ithe imost iregularly iutilized ionline inetworking iareas iwhere iindividuals ivoice itheir isentiments ion iattractive imuch ieverything. isuch ia isignificant inumber iof ispecialist iorganizations itake ithe istage ito iadvance itheir iadministrations iamong ithe iclients. iMedia itransmission isection iis ione iof ithem. iIt iis ivery ievident ithat inumerous iTelecommunication iorganization ikeeps iup ia iFacebook ipage ior igathering ito iraise itheir imanagements ito ithe iclients iand iget idisapproval ifrom ithem. iLimitless iis ibeing idelivered ialong ithese ilines ievery iday. In ithis ithesis, iwe iwill iseparate ievery ione iof ithe isentiments i(remarks ias icontent iinformation) ifrom ieach iindividual iprofile ipages iutilizing iFacebook igraph iAPI iis igiven iby iFacebook iapplication i& iexperience icommotion iscrubbing, iapplying isentiment i& iclassifier ifor icomputing iopinion iextremity igo ito ichoice iwhether ioffers iare igiven iby iorganization iis ireceiving igreat iinput ior inot. iAnd iin ithis ithesis ifor iour isentiment ianalysis iI iused inaïve iBayes iclassifier itechniques.