Summarizing Opinions with Sentiment Analysis from Multiple Reviews on Travel Destinations

Argha Roy, Shyamali Guria, Suman Halder, Sayani Banerjee and Sourav Mandal
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Argha Roy: Haldia Institute of Technology, Haldia, India
Shyamali Guria: Haldia Institute of Technology, Haldia, India
Suman Halder: Haldia Institute of Technology, Haldia, India
Sayani Banerjee: Haldia Institute of Technology, Haldia, India
Sourav Mandal: Haldia Institute of Technology, Haldia, India

International Journal of Synthetic Emotions (IJSE), 2018, vol. 9, issue 2, 111-120

Abstract: Recently, the web has been crowded with growing volumes of various texts on every aspect of human life. It is difficult to rapidly access, analyze, and compose important decisions using efficient methods for raw textual data in the form of social media, blogs, feedback, reviews, etc., which receive textual inputs directly. It proposes an efficient method for summarization of various reviews of tourists on a specific tourist spot towards analyzing their sentiments towards the place. A classification technique automatically arranges documents into predefined categories and a summarization algorithm produces the exact condensed input such that output is most significant concepts of source documents. Finally, sentiment analysis is done in summarized opinion using NLP and text analysis techniques to show overall sentiment about the spot. Therefore, interested tourists can plan to visit the place do not go through all the reviews, rather they go through summarized documents with the overall sentiment about target place.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jse000:v:9:y:2018:i:2:p:111-120

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