Twitter Sentiment Classification on Sanders Data using HybridApproach
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 4
Abstract
Abstract : Sentiment analysis is very perplexing and massive issue in the field of social data mining. Twitter isone of the mostly used social media where people discuss on various issues in a dense way. The tweets about aparticular topic give peoples’ views, opinions, orientations, inclinations about that topic. In this work, we haveused pre-labeled (with positive, negative and neutral opinion) tweets on particular topics for sentimentclassification. Opinion score of each tweet is calculated using feature vectors. These opinion score is used toclassify the tweets into positive, negative and neutral classes. Then using various machine learning classifiersthe accuracy of predicted classification with respect to actual classification is being calculated and comparedusing supervised learning model. Along with building a sentiment classification model, analysis of tweets is being carried out by visualizing the wordcloud of tweets using R.
Authors and Affiliations
Kishori K. Pawar , R. R. Deshmukh
Keywords
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