Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10197
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dc.contributor.authorSrivastava, Aryan-
dc.contributor.authorSingh, Hari [Guided by]-
dc.date.accessioned2023-09-30T10:09:54Z-
dc.date.available2023-09-30T10:09:54Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10197-
dc.descriptionEnrollment No. 191322en_US
dc.description.abstractSentiment Analysis has grown to be a fascinating area in both academic and commercial settings. The word sentiment describes how a person feels or thinks about a certain problem. It's seen as a direct application of opinion mining as well. Twitter is a rich source of textual data and one of the most important data volumes due to the enormous volume of tweets written down each day; as a result, this data has various goals depending on the amount of data needed and the processing that will be required, such as business, industrial, or social goals. Actually, the enormous volume of data, known as big data, is growing quickly every second, necessitating the use of advanced processing methods and powerful computers to carry out the necessary mining activities.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectSentiment analysisen_US
dc.subjectTwitteren_US
dc.subjectN-gram modelen_US
dc.titleSpark based N-gram model for Sentiment Analysis on Twitter Dataseten_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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