Automatic analysis of textual hotel reviews

Aitor García-Pablos (), Montse Cuadros () and Maria Teresa Linaza ()
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Aitor García-Pablos: Vicomtech-IK4
Montse Cuadros: Vicomtech-IK4
Maria Teresa Linaza: Vicomtech-IK4

Information Technology & Tourism, 2016, vol. 16, issue 1, No 4, 45-69

Abstract: Abstract Social Media and consumer-generated content continue to grow and impact the hospitality domain. Consumers write online reviews to indicate their level of satisfaction with a hotel and inform other consumers on the Internet of their hotel stay experience. A number of websites specialized in tourism and hospitality have flourished on the Web (e.g. Tripadvisor). The tremendous growth of these data-generating sources demands new tools to deal with them. To cope with big amounts of customer-generated reviews and comments, Natural Language Processing (NLP) tools have become necessary to automatically process and manage textual customer reviews (e.g. to perform Sentiment Analysis). This work describes OpeNER, a NLP platform applied to the hospitality domain to automatically process customer-generated textual content and obtain valuable information from it. The presented platform consists of a set of Open Source and free NLP tools to analyse text based on a modular architecture to ease its modification and extension. The training and evaluation has been performed using a set of manually annotated hotel reviews gathered from websites like Zoover and HolidayCheck.

Keywords: Customer-generated reviews; Text analysis; Sentiment analysis (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s40558-015-0047-7

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