Twitter Real Time Review Report Generator

dc.contributor.authorCHAYA CHANDRASHEKAR, SHETTY
dc.contributor.authorCHETANA M, JYOTHI
dc.contributor.authorJYOTHI
dc.contributor.authorNAYANA, M M
dc.date.accessioned2018-06-19T09:05:16Z
dc.date.available2018-06-19T09:05:16Z
dc.date.issued2018-06-19T09:05:16Z
dc.description.abstractIn general, opinion mining has been used to know about what people think and feel about their products and services in social media platforms. Millions of users share opinions on different aspects of life every day. Spurred by that growth, companies andmedia organizations are increasingly seeking way to mine information. It requires efficient techniques to collect a large amount of social media data and extract meaningful information from them. Till now, there are few different problems predominating in this research community, namely, sentiment classification, feature based classification and handling negations. A precise method is used for predicting sentiment polarity, which helps to improve marketing strategies. This paper deals withthe challenges that appear in the process of Sentiment Analysis, real time tweets are considered as they are rich sources of data for opinion mining and sentiment analysis. This paper focus on Sentiment analysis, Feature based Sentiment classification and Opinion Summarization. The main objective of this paper is to perform real time sentimental analysis on the tweets that are extracted from the twitter and provide time based analytics to the user.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/9421
dc.language.isoenen_US
dc.subjectCHAYA CHANDRASHEKAR SHETTYen_US
dc.subjectCHETANA M JYOTHIen_US
dc.subjectJYOTHIen_US
dc.subjectNAYANA M Men_US
dc.subject1NH14CS024en_US
dc.subject1NH14CS025en_US
dc.subject1NH14CS050en_US
dc.subject1NH14CS076en_US
dc.titleTwitter Real Time Review Report Generatoren_US
dc.typeOtheren_US
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