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dc.contributor.authorHOODA, PARUL-
dc.date.accessioned2017-07-14T12:02:32Z-
dc.date.available2017-07-14T12:02:32Z-
dc.date.issued2017-06-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/repository/15810-
dc.description.abstractSentiment analysis (also known as opinion mining) refers to the use of natural language processing (NLP), text analysis and computational linguistics to identify and extract subjective information from the source materials. Generally speaking, sentiment analysis aims to determine the attitude of a writer or a speaker with respect to a specific topic or the overall contextual polarity of a document. Globally, business enterprises can leverage opinion polarity and sentiment topic recognition to gain deeper understanding of the drivers and the overall scope. Subsequently, these insights can advance competitive intelligence and improve customer service, thereby creating a better brand image and providing a competitive edge. The e-commerce industry is benefiting greatly by utilizing sentiment analysis. Generally, on e-commerce portals, buyers often express their opinions in the form of comments (positive or negative) for the products they have purchased, making this a huge data trove for sentiment analysis. Correspondingly, analysis of such opinion-related data (comments) can provide deep-insights to the key stakeholders. A thorough sentiment analysis reveals deep-insights on the product, quality and performance. Additional insights that can be extracted using sentiment analysis include.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTD 2783;-
dc.subjectSENTIMENT ANALYSISen_US
dc.subjectBRAND MANAGEMENTen_US
dc.subjectNLPen_US
dc.titleSENTIMENT BASED TOOL FOR BRAND MANAGEMENTen_US
dc.typeThesisen_US
Appears in Collections:M.E./M.Tech. Information Technology

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