Multi-Language Sentiment Analysis for Hotel Reviews

Multi-Language Sentiment Analysis for Hotel Reviews

Touristes and traveler use avariety of information sources (e.g. travelportals, blogs, or social networking sites like twitter) to help them decide for a hotel room. These sources all contain highly subjective text that expresses the opinions of many. We took a preliminary view on user generated hot...

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Main Author: Sodanil Maleerat
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:MATEC Web of Conferences
Online Access:http://dx.doi.org/10.1051/matecconf/20167503002
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spelling doaj-865d95b50dd142659aef2745d32946bc2021-02-02T03:57:10ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01750300210.1051/matecconf/20167503002matecconf_icmie2016_03002Multi-Language Sentiment Analysis for Hotel ReviewsSodanil MaleeratTouristes and traveler use avariety of information sources (e.g. travelportals, blogs, or social networking sites like twitter) to help them decide for a hotel room. These sources all contain highly subjective text that expresses the opinions of many. We took a preliminary view on user generated hotel reviews from two travel portals in English and Thai. We developed a taxonomy of features and specifically investigated how accurately they can be predicted with three classification methods. The results indicate that support vector machines perform best for this specific domain.http://dx.doi.org/10.1051/matecconf/20167503002
collection DOAJ
language English
format Article
sources DOAJ
author Sodanil Maleerat
spellingShingle Sodanil Maleerat
Multi-Language Sentiment Analysis for Hotel Reviews
MATEC Web of Conferences
author_facet Sodanil Maleerat
author_sort Sodanil Maleerat
title Multi-Language Sentiment Analysis for Hotel Reviews
title_short Multi-Language Sentiment Analysis for Hotel Reviews
title_full Multi-Language Sentiment Analysis for Hotel Reviews
title_fullStr Multi-Language Sentiment Analysis for Hotel Reviews
title_full_unstemmed Multi-Language Sentiment Analysis for Hotel Reviews
title_sort multi-language sentiment analysis for hotel reviews
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2016-01-01
description Touristes and traveler use avariety of information sources (e.g. travelportals, blogs, or social networking sites like twitter) to help them decide for a hotel room. These sources all contain highly subjective text that expresses the opinions of many. We took a preliminary view on user generated hotel reviews from two travel portals in English and Thai. We developed a taxonomy of features and specifically investigated how accurately they can be predicted with three classification methods. The results indicate that support vector machines perform best for this specific domain.
url http://dx.doi.org/10.1051/matecconf/20167503002
work_keys_str_mv AT sodanilmaleerat multilanguagesentimentanalysisforhotelreviews
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