Abstract
An enormous growth of the WWW has been instrumental in spreading social networks. Due to many-fold increase in internet users taking to online reviews and opinions, the communication, sharing and collaboration through social networks have gained importance. The rapid growth in web-based activities has led to generation of huge amount of unstructured data which accounts for over 80% of the information. Exploiting big data alternatives in storing, processing, archiving and analyzing this data becomes increasingly necessary.
In this paper we propose a generalized approach to analyzing sentiments in big-data environment. The proposed model would serve to incorporate different supervised and un-supervised approaches to extraction, classification and scoring of opinions and sentiment words.
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Borikar, D.A., Chandak, M.B. (2016). An Approach to Sentiment Analysis on Unstructured Data in Big Data Environment. In: Unal, A., Nayak, M., Mishra, D.K., Singh, D., Joshi, A. (eds) Smart Trends in Information Technology and Computer Communications. SmartCom 2016. Communications in Computer and Information Science, vol 628. Springer, Singapore. https://doi.org/10.1007/978-981-10-3433-6_21
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DOI: https://doi.org/10.1007/978-981-10-3433-6_21
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