OpinionSeer: Interactive Visualization of Hotel Customer Feedback

The rapid development of Web technology has resulted in an increasing number of hotel customers sharing their opinions on the hotel services. Effective visual analysis of online customer opinions is needed, as it has a significant impact on building a successful business. In this paper, we present OpinionSeer, an interactive visualization system that could visually analyze a large collection of online hotel customer reviews. The system is built on a new visualization-centric opinion mining technique that considers uncertainty for faithfully modeling and analyzing customer opinions. A new visual representation is developed to convey customer opinions by augmenting well-established scatterplots and radial visualization. To provide multiple-level exploration, we introduce subjective logic to handle and organize subjective opinions with degrees of uncertainty. Several case studies illustrate the effectiveness and usefulness of OpinionSeer on analyzing relationships among multiple data dimensions and comparing opinions of different groups. Aside from data on hotel customer feedback, OpinionSeer could also be applied to visually analyze customer opinions on other products or services.

[1]  Chaomei Chen,et al.  Visual Analysis of Conflicting Opinions , 2006, 2006 IEEE Symposium On Visual Analytics Science And Technology.

[2]  Daniel A. Keim,et al.  Visual Sentiment Analysis of RSS News Feeds Featuring the US Presidential Election in 2008 , 2009 .

[3]  Eric K. Ringger,et al.  Pulse: Mining Customer Opinions from Free Text , 2005, IDA.

[4]  Colin Ware,et al.  Information Visualization: Perception for Design , 2000 .

[5]  Bing Liu,et al.  Mining and summarizing customer reviews , 2004, KDD.

[6]  Matthew O. Ward,et al.  InterRing: an interactive tool for visually navigating and manipulating hierarchical structures , 2002, IEEE Symposium on Information Visualization, 2002. INFOVIS 2002..

[7]  Richard F. Riesenfeld,et al.  Who Votes For What? A Visual Query Language for Opinion Data , 2008, IEEE Transactions on Visualization and Computer Graphics.

[8]  Dimitrios Buhalis,et al.  The Impact of Culture on eComplaints: Evidence from Chinese Consumers in Hospitality Organisations , 2010, ENTER.

[9]  Michelle L. Gregory,et al.  User-directed Sentiment Analysis: Visualizing the Affective Content of Documents , 2006 .

[10]  Clark Hu,et al.  Analyzing Hotel Customers' E-Complaints from an Internet Complaint Forum , 2004 .

[11]  Furu Wei,et al.  Context preserving dynamic word cloud visualization , 2010, 2010 IEEE Pacific Visualization Symposium (PacificVis).

[12]  LeeLillian,et al.  Opinion Mining and Sentiment Analysis , 2008 .

[13]  Richard F. Riesenfeld,et al.  A Survey of Radial Methods for Information Visualization , 2009, IEEE Transactions on Visualization and Computer Graphics.

[14]  Kau Ah Keng,et al.  Determinants of Consumer Complaint Behaviour , 1995 .

[15]  Martin Wattenberg,et al.  Participatory Visualization with Wordle , 2009, IEEE Transactions on Visualization and Computer Graphics.

[16]  Daniel A. Keim,et al.  Visual opinion analysis of customer feedback data , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[17]  Bing Liu,et al.  Mining Opinion Features in Customer Reviews , 2004, AAAI.

[18]  J. Wooders,et al.  Reputation in Auctions: Theory, and Evidence from Ebay , 2006 .

[19]  Bing Liu,et al.  Opinion Mining , 2009, Encyclopedia of Database Systems.

[20]  Kwan-Liu Ma,et al.  A framework for uncertainty-aware visual analytics , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[21]  Bernice E. Rogowitz,et al.  How not to lie with visualization , 1996 .

[22]  Dimitrios Buhalis,et al.  Complaints on the Online Environment - The Case of Hong Kong Hotels , 2009, ENTER.

[23]  Helwig Hauser,et al.  Parallel Sets: interactive exploration and visual analysis of categorical data , 2006, IEEE Transactions on Visualization and Computer Graphics.

[24]  Lillian Lee,et al.  Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..

[25]  Oren Etzioni,et al.  Extracting Product Features and Opinions from Reviews , 2005, HLT.

[26]  Soo-Min Kim,et al.  Determining the Sentiment of Opinions , 2004, COLING.

[27]  Satoshi Morinaga,et al.  Mining product reputations on the Web , 2002, KDD.

[28]  Bo Pang,et al.  Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.

[29]  Bing Liu,et al.  Opinion observer: analyzing and comparing opinions on the Web , 2005, WWW '05.

[30]  Michael Gamon,et al.  BLEWS: Using Blogs to Provide Context for News Articles , 2008, ICWSM.

[31]  I. Vermeulen,et al.  Tried and tested: The impact of online hotel reviews on consumer consideration , 2009 .

[32]  Audun Jøsang,et al.  The consensus operator for combining beliefs , 2002, Artif. Intell..