Sentiment analysis and text summarization has evoke the interest of many scientists and researchers in last few years, since the textual data has become useful for many real world applications and problems. Sentiment analysis is a machine learning approach in which machine learns and analyze the sentiments, emotions etc about some text data like reviews about movies or products. These reviews are increasing day by day, due to which summarization of reviews comes in role where summarized form of text in needed, which provides useful information from the large number of reviews. It is very difficult for a human being to extract useful data or summarize it from the very large document. In Text summarization, importance of sentences is decided based on linguistic features of sentences. This paper provides the comprehensive overview of recent and past research on sentiment analysis and text summarization and provides excellent research queries and approaches for future aspects.
CITATION STYLE
Gupta, P., Tiwari, R., & Robert, N. (2016). Sentiment analysis and text summarization of online reviews: A survey. In International Conference on Communication and Signal Processing, ICCSP 2016 (pp. 241–245). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICCSP.2016.7754131
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