Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/7752
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dc.contributor.authorGupta, Abhinav Kirti-
dc.contributor.authorChauhan, Abhimanyu-
dc.contributor.authorSingh, Hari [Guided by]-
dc.date.accessioned2022-10-13T07:16:20Z-
dc.date.available2022-10-13T07:16:20Z-
dc.date.issued2019-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/7752-
dc.description.abstractThis project addresses the problem of sentiment analysis in twitter; that is classifying tweets according to the sentiment expressed in them: positive, negative or neutral. Twitter is an online micro-blogging and social-networking platform which allows users to write short status updates of maximum length 140 characters. It is a rapidly expanding service with over 200 million registered users - out of which 100 million are active users and half of them log on twitter on a daily basis - generating nearly 250 million tweets per day. Due to this large amount of usage we hope to achieve a reflection of public sentiment by analyzing the sentiments expressed in the tweets. Analyzing the public sentiment is important for many applications such as firms trying to find out the response of their products in the market, predicting political elections and predicting socioeconomic phenomena like stock exchange. The aim of this project is to develop a functional classifier for accurate and automatic sentiment classification of an unknown tweet stream.en_US
dc.language.isoenen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectTwitteren_US
dc.subjectSentimental analysisen_US
dc.titleTwitter Sentimental Analysisen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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