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Multi-dimension reviewer credibility quantification across diverse travel communities

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Abstract

The rapid development of social media technologies enables travellers to share travel experiences and opinions online by posting reviews, which then serve as information source for other travellers. However, the explosive growth of reviews and the proliferation of uninformative, biased or even false information make it very challenging for travellers to find credible information. To help travellers seek credible information, most current work apply mainly qualitative approaches to investigate the credibility of reviews or reviewers. This paper adopts an Impact Index to quantify the credibility of reviewers by simultaneously evaluating the expertise and trustworthiness of reviewers based on the number of reviews posted by them and the number of helpful votes received by those reviews. Furthermore, the Impact Index is enhanced into the Exposure-Impact Index by considering in addition reviewers’ breadth of expertise in the form of the number of destinations on which reviewers posted reviews. To examine the effectiveness and applicability of Impact Index and Exposure-Impact Index, this paper evaluates them on several data sets collected from two rather different online travel communities: TripAdvisor, the world’s largest travel community, and Qunar, one of the most popular travel communities in China. Experimental results show that both Impact Index and Exposure-Impact Index lead to more consistent results with human judgments than the state-of-the-art method in measuring the credibility of reviewers from diverse communities, manifesting their effectiveness and applicability.

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Notes

  1. TripAdvisor.com, Fact Sheet. http://www.tripadvisor.com/pressCenter-c4-Fact_Sheet.html.

  2. http://www.qunar.com/site/zh/zhMilestones.shtml.

  3. TripAdvisor Trends: http://www.onecaribbean.org/wp-content/uploads/CTOTripAdvisorCWeek2013Paganelli.pdf.

  4. TripAdvisor Trends: http://www.onecaribbean.org/wp-content/uploads/CTOTripAdvisorCWeek2013Paganelli.pdf.

  5. Source: Google Analytics, worldwide data, July 2013.

  6. Financial Tear Sheet - Qunar, http://investor.qunar.com/Tearsheet.ashx?c=252141.

  7. http://investor.qunar.com/phoenix.zhtml?c=252141&p=irol-govmilestone_pf.

  8. http://edition.cnn.com/2014/03/09/travel/tripadvisor-decoded/index.html?hpt=hp_c5.

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Acknowledgments

This project was partially supported by Hong Kong Research Grants Council, which number is PolyU 5116/08(B-Q13F).

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Authors and Affiliations

  1. Shenzhen University, Shenzhen, Guangdong, China

    Yuanyuan Wang

  2. Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China

    Yuanyuan Wang, Stephen Chi Fai Chan, Hong Va Leong & Grace Ngai

  3. School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China

    Norman Au

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  1. Yuanyuan Wang
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Correspondence to Yuanyuan Wang.

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Wang, Y., Chan, S.C.F., Leong, H.V. et al. Multi-dimension reviewer credibility quantification across diverse travel communities. Knowl Inf Syst 49, 1071–1096 (2016). https://doi.org/10.1007/s10115-016-0927-y

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