Aspect based sentiment analysis of hotels and its business applications (CD)

By: Yadhav, Kanakarajulu Suneel Kumar
Contributor(s): K, Chandra Sekhar [Co-author] | S, Hemanth Kumar [Co-author]
Material type: Computer fileComputer filePublisher: Ahmedabad Indian Institute of Management Ahmedabad 2017Description: 20 p.: col. ill. Includes bibliographical references Subject(s): Sentiment analysis - Hotels | Business application | E-commerceDDC classification: SP2017/2380 Online resources: e-Report Summary: With the rapid increase in internet usage, customers found online sources as excellent platforms for providing their opinions / reviews / feedback and these data is growing over time by serving as wonderful source for information. On one side, these data helps customers to make wise purchasing decisions and on other side, management could use this data effectively for improving their business. In this project, we try to help the hotel management by extracting hotel reviews from online websites and find out the performance of hotels by conducting aspect based sentiment analysis. The sentiment scores extracted from the sentiment analysis are used to explore effective data visualizations and business applications.
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Student Project Vikram Sarabhai Library
Audio Visual
Non-fiction SP2017/2380 (Browse shelf) Not for Issue SP002380

Submitted to Prof. Srikumar Krishnamoorthy
Submitted by PGP 2016-2018 batch in 5th term

With the rapid increase in internet usage, customers found online sources as excellent platforms for providing their opinions / reviews / feedback and these data is growing over time by serving as wonderful source for information. On one side, these data helps customers to make wise purchasing decisions and on other side, management could use this data effectively for improving their business. In this project, we try to help the hotel management by extracting hotel reviews from online websites and find out the performance of hotels by conducting aspect based sentiment analysis. The sentiment scores extracted from the sentiment analysis are used to explore effective data visualizations and business applications.

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