Abstract
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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The authors thank the anonymous reviewers for their valuable suggestions that have helped in improving the paper.
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Mangal, N., Niyogi, R., Milani, A. (2016). Analysis of Users’ Interest Based on Tweets. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9790. Springer, Cham. https://doi.org/10.1007/978-3-319-42092-9_2
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DOI: https://doi.org/10.1007/978-3-319-42092-9_2
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