Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/5937
Title: Emotion Classification on Social Networking Sites
Authors: Vadehra, Geetanjali
Kumar, Pardeep [Guided by]
Keywords: Sentiment analysis
Machine learning
Social networking
Issue Date: 2015
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: Sentiment Analysis (SA) is an ongoing field of research in text mining field. SA is the computational treatment of opinions, sentiments and subjectivity of text. The decision-making process of people is affected by the opinions formed by thought leaders and ordinary people. When a person wants to buy a product online he or she will typically start by searching for reviews and opinions written by other people on the various offerings. Sentiment analysis is one of the hottest research areas in computer science. Over 7,000 articles have been written on the topic. Hundreds of startups are developing sentiment analysis solutions and major statistical packages such as SAS and SPSS include dedicated sentiment analysis modules. There is a huge explosion today of 'sentiments' available from social media including Twitter, Facebook, message boards, blogs, and user forums. These snippets of text are a gold mine for companies and individuals that want to monitor their reputation and get timely feedback about their products and actions. Sentiment analysis offers these organizations the ability to monitor the different social media sites in real time and act accordingly. Marketing managers, PR firms, campaign managers, politicians, and even equity investors and online shoppers are the direct beneficiaries of sentiment analysis technology.
URI: http://ir.juit.ac.in:8080/jspui//xmlui/handle/123456789/5937
Appears in Collections:B.Tech. Project Reports

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