Analysis of tweets would help in designing smart recommendation systems. Analysis of twitter messages is an interesting research area. Sentiment analysis of tweets has been done in some works. Another line of work is the classification of tweets into different categories. However, there are few works that have considered both sentiment analysis and classification to find out users’ interest. In this paper, we propose an approach that combines both sentiment analysis and classification. Thus we are able to extract the topic in which users are interested. We have implemented our algorithm using five lakhs of tweets and around one thousand of users. The results are quite encouraging
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L. Gavrilova. (2006). Spatial Modeling and Geovisualization of Rental Prices for Real Estate Portals Harald (Vol. 1, p. 354).
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