Application of social media analytics: a case of analyzing online hotel reviews
| Pages | 921-935 |
| DOI | https://doi.org/10.1108/OIR-07-2016-0201 |
| Published date | 13 November 2017 |
| Date | 13 November 2017 |
| Author | Wu He,Xin Tian,Ran Tao,Weidong Zhang,Gongjun Yan,Vasudeva Akula |
| Subject Matter | Library & information science,Information behaviour & retrieval,Collection building & management,Bibliometrics,Databases,Information & knowledge management,Information & communications technology,Internet,Records management & preservation,Document management |
Application of social media
analytics: a case of analyzing
online hotel reviews
Wu He
Old Dominion University, Norfolk, Virginia, USA
Xin Tian
College of Business and Public Administration,
Old Dominion University, Norfolk, Virginia, USA
Ran Tao
Department of Computer Science, Donghua University, Shanghai, China
Weidong Zhang
Department of Information Management,
Jilin University, Changchun, China
Gongjun Yan
Romain College of Business, University of Southern Indiana,
Evansville, Indiana, USA, and
Vasudeva Akula
VOZIQ Company, Reston, Virginia, USA
Abstract
Purpose –Online customer reviews could shed light into their experience, opinions, feelings, and concerns.
To gain valuable knowledge about customers, it becomes increasingly important for businesses to collect,
monitor, analyze, summarize, and visualize online customer reviews posted on social media platforms such as
online forums. However, analyzing social media data is challenging due to the vast increase of social media
data. The purpose of this paper is to present an approach of using natural language preprocessing, text
mining and sentiment analysis techniques to analyze online customer reviews related to various hotels
through a case study.
Design/methodology/approach –This paper presents a tested approach of using natural language
preprocessing, text mining, and sentiment analysis techniques to analyze online textual content. The value of
the proposed approach was demonstrated through a case study using online hotel reviews.
Findings –The study found that the overall review star rating correlates pretty well with the sentiment
scores for both the title and the full content of the online customer review. The case study also revealed that
both extremely satisfied and extremely dissatisfied hotel customers share a common interest in the five
categories: food, location, rooms, service, and staff.
Originality/value –This study analyzed the online reviews from English-speaking hotel customers in
China to understand their preferred hotel attributes, main concerns or demands. This study also provides a
feasible approach and a case study as an example to help enterprises more effectively apply social media
analytics in practice.
Keywords Sentiment analysis, Social media analytics, Text mining, Online hotel reviews,
User-generated data
Paper type Case study
1. Introduction
Numerous businesses are involved in online activities by using different social media
platforms such as Twitter and Facebook. Comments on social media are a source of
information increasingly taken into account by the end customer and businesses.
Businesses are increasingly considering social media data as a valuable and timely
Online Information Review
Vol. 41 No. 7, 2017
pp. 921-935
© Emerald PublishingLimited
1468-4527
DOI 10.1108/OIR-07-2016-0201
Received 30 July 2016
Revised 21 December 2016
8 April 2017
8 July 2017
Accepted 8 July 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1468-4527.htm
921
Application of
social media
analytics
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