Knowledge and Information Systems

, Volume 49, Issue 3, pp 1071–1096 | Cite as

Multi-dimension reviewer credibility quantification across diverse travel communities

  • Yuanyuan Wang
  • Stephen Chi Fai Chan
  • Hong Va Leong
  • Grace Ngai
  • Norman Au
Regular Paper


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.


Reviewer credibility Credible review Tourism 



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


  1. 1.
    Sparks BA, Browning V (2011) The impact of online reviews on hotel booking intentions and perception of trust. Tour Manag 32(6):1310–1323CrossRefGoogle Scholar
  2. 2.
    Kusumasondjaja S, Shanka T (2012) Credibility of online reviews and initial trust: the roles of reviewer’s identity and review valence. J Vacat Mark 18(3):185–195CrossRefGoogle Scholar
  3. 3.
    Loda MD (2011) Comparing web sites: an experiment in online tourism marketing. Int J Bus Soc Sci 2(22):70–78Google Scholar
  4. 4.
    Long C, Zhang J, Huang M, Zhu X, Li M, Ma B (2014) Estimating feature ratings through an effective review selection approach. Knowl Inf Syst 38(2):419–446CrossRefGoogle Scholar
  5. 5.
    Kurashima T, Iwata T, Irie G, Fujimura K (2013) Travel route recommendation using geotagged photos. Knowl Inf Syst 37(1):37–60CrossRefGoogle Scholar
  6. 6.
    Metzger MJ, Flangin AJ, Eyal K, Lemus DR, McCann RM (2003) Credibility for the 21st century: integrating perspectives on source, message, and media credibility in the contemporary media environment. Commun Yearb 27:293–335CrossRefGoogle Scholar
  7. 7.
    Yoo KH, Gretzel U (2009) Comparison of deceptive and truthful travel reviews. Information and Communication Technologies in Tourism 2009: Proceedings of the International Conference, Jan 28–30, Amsterdam, Netherlands, pp 37–47Google Scholar
  8. 8.
    Lee H, Law R, Murphy J (2011) Helpful reviewers in TripAdvisor: an online travel community. J Travel Tour Mark 28(7):67–88Google Scholar
  9. 9.
    Metzger MJ, Flanagin AJ, Medders R (2010) Social and heuristic approaches to credibility evaluation online. J Commun 60(3):413–439CrossRefGoogle Scholar
  10. 10.
    Gretzel U, Yoo KH, Purifoy M (2007) Online travel review study: role and impact of online travel reviews. Laboratory for Intelligent Systems in Tourism, Texas A&M University, College StationGoogle Scholar
  11. 11.
    Xie H, Miao L, Kuo PJ, Lee BY (2011) Consumers’ responses to ambivalent online hotel reviews: the role of perceived source credibility and pre-decisional disposition. Int J Hosp Manag 30(1):178–183CrossRefGoogle Scholar
  12. 12.
    Rieh SY, Danielson DR (2007) Credibility: a multidisciplinary framework. Annu Rev Inf Sci Technol 41(1):307–364CrossRefGoogle Scholar
  13. 13.
    Fragale AR, Heath C (2004) Evolving information credentials: the (mis) attribution of believable facts to credible sources. Pers Soc Psychol Bull 30(2):225–236CrossRefGoogle Scholar
  14. 14.
    Vermeulen IE, Seegers D (2009) Tried and tested: the impact of online hotel reviews on consumer consideration. Tour Manag 30(1):123–127CrossRefGoogle Scholar
  15. 15.
    Yoo KH, Lee KS, Gretzel U (2007) The role of source characteristics in eWOM: what makes online travel reviewers credible and likeable. In: The 14th international conference on information technology and travel and tourism, Jan 24–26, Ljubljana, Slovenia, pp 23–34Google Scholar
  16. 16.
    Park H, Xiang Z, Josiam B, Kim H (2014) Personal profile information as cues of credibility in online travel reviews. Anatolia 25(1):13–23CrossRefGoogle Scholar
  17. 17.
    Flanagin AJ, Metzger MJ (2008) Digital media and youth: unparalleled opportunity and unprecedented responsibility. In: Metzger M, Flanagin A (eds) Digital media, youth, and Credibility, MacArthur foundation series on digital media and learning. The MIT Press, Cambridge, pp 5–27Google Scholar
  18. 18.
    Hovland CI, Janis IL, Kelley HH (1953) Communication and persuasion: psychological studies of opinion change. Yale University Press, New Haven, CTGoogle Scholar
  19. 19.
    Wang Y, Chan SCF, Ngai G, Leong HV (2013) Quantifying reviewer credibility in online tourism. Database and expert systems applications, Aug 26–30. Czech Republic, Prague, pp 381–395CrossRefGoogle Scholar
  20. 20.
    Sidali KL, Schulze H, Spiller A (2009) The impact of online reviews on the choice of holiday accommodations. Information and Communication Technologies in Tourism 2009: Proceedings of the International Conference, Jan 28–30, Amsterdam, Netherlands, pp 87–98Google Scholar
  21. 21.
    Mauri AG, Minazzi R (2013) Web reviews influence on expectations and purchasing intentions of hotel potential customers. Int J Hosp Manag 34:99–107CrossRefGoogle Scholar
  22. 22.
    Pornpitakpan C (2004) The persuasiveness of source credibility: a critical review of five decades’ evidence. J Appl Soc Psychol 34(2):243–281CrossRefGoogle Scholar
  23. 23.
    Hochmeister M, Gretzel U, Werthner H (2013) Destination expertise in online travel communities. Information and Communication Technologies in Tourism 2013: Proceedings of the International Conference, Jan 22–25, Innsbruck, Austria, pp 218–229Google Scholar
  24. 24.
    Yoo KH, Lee Y, Gretzel U, Fesenmaier DR (2009) Trust in Travel-related Consumer Generated Media. Information and Communication Technologies in Tourism 2009: Proceedings of the International Conference, Jan 28–30, Amsterdam, Netherlands, pp 49–60Google Scholar
  25. 25.
    Suomi R, Li H (2008) Internet adoption in tourism industry in China. The 8th IFIP Conference on e-Business, e-Services, and e-Society, Sept 24–16. Tokyo, Japan, pp 197–208Google Scholar
  26. 26.
    Budde F, Tranter P, Fechtel A, Wise A, Lui V, Milunsky T (2013) Winning the next billion AsianTravelers-Starting with China. The Boston Consulting Group,
  27. 27.
    Cho J, Kwon K, Park Y (2009) Q-rater: a collaborative reputation system based on source credibility theory. Expert Syst Appl 36(2):3751–3760CrossRefGoogle Scholar
  28. 28.
    Hirsch JE (2005) An index to quantify an individual’s scientific research output. Proc Natl Acad Sci USA 102(46):16569–16572CrossRefGoogle Scholar
  29. 29.
    Jeacle I, Carter C (2011) In TripAdvisor we trust: rankings, calculative regimes and abstract systems. Account Organ Soc 36(4):293–309CrossRefGoogle Scholar
  30. 30.
    Steven M (2012) TripAdvisor Under Fire for ‘Real Traveller’ Contribution Claim. Feb 1, The Guardian,
  31. 31.
    Mayzli D, Dover Y, Chevalier JA (2012) Promotional reviews: An empirical investigation of online review manipulation. National Bureau of Economic Research, Aug 13, Working paper No. 18340,
  32. 32.
    Feng VW, Hirst G (2013) Detecting deceptive opinions with profile compatibility. In: The 6th international joint conference on natural language processing, Oct 14–18, Nagoya, Japan, pp 14–18Google Scholar
  33. 33.
    Li J, Ott M, Cardie C (2013) Identifying manipulated offerings on review portals. In: Conference on empirical methods in natural language processing, Oct 18–21, Seattle, USA, pp 1933–1942Google Scholar
  34. 34.
    Mukherjee A, Venkataraman V, Liu B, Glance NS (2013) What yelp fake review filter might be doing. In: Seventh international AAAI conference on weblogs and social media, Jul 8–11, Boston, USA, pp 409–418Google Scholar
  35. 35.
    Ott M, Choi Y, Cardie C, Hancock, JT (2011) Finding deceptive opinion spam by any stretch of the imagination. In: The 49th annual meeting of the association for computational linguistics, Jun 19–24, Portland, Oregon, USA, pp 309–319Google Scholar
  36. 36.
    Li J, Ott M, Cardie C, Hovy, E (2014) Towards a General Rule for Identifying Deceptive Opinion Spam. In: The 52nd annual meeting of the association for computational linguistics, Jun 23–25, Baltimore, Maryland, USA, pp 1566–1576Google Scholar
  37. 37.
    Redner S (1998) How popular is your paper? An empirical study of the citation distribution. Eur Phys J B Condens Matter Complex Syst 4(2):131–134CrossRefGoogle Scholar
  38. 38.
    Clauset A, Shalizi CR, Newman ME (2009) Power-law distributions in empirical data. Soc Ind Appl Math 51(4):661–703MathSciNetzbMATHGoogle Scholar
  39. 39.
    Newman ME (2005) Power laws, Pareto distributions and Zipf’s law. Contemp Phys 46(5):323–351CrossRefGoogle Scholar
  40. 40.
    Kubiszewski I, Noordewier T, Costanza R (2011) Perceived credibility of internet encyclopedias. Comput Educ 56(3):659–667CrossRefGoogle Scholar
  41. 41.
    Schwarz J, Morris M (2011) Augmenting web pages and search results to support credibility assessment. In: The SIGCHI conference on human factors in computing systems, May 7–12, Vancouver, BC, Canada, pp 1245–1254Google Scholar
  42. 42.
    Chen CC, Tseng YD (2011) Quality evaluation of product reviews using an information quality framework. Decis Support Syst 50(4):755–768CrossRefGoogle Scholar
  43. 43.
    Savolainen R (2011) Judging the quality and credibility of information in Internet discussion forums. J Am Soc Inf Sci Technol 62(7):1243–1256CrossRefGoogle Scholar
  44. 44.
    Bargagliotti AE, Greenwell RN (2011) Statistical significance of ranking paradoxes. Commun Stat Theory and Methods 40(5):916–928MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  • Yuanyuan Wang
    • 1
    • 2
  • Stephen Chi Fai Chan
    • 2
  • Hong Va Leong
    • 2
  • Grace Ngai
    • 2
  • Norman Au
    • 3
  1. 1.Shenzhen UniversityShenzhenChina
  2. 2.Department of ComputingThe Hong Kong Polytechnic UniversityHung Hom, KowloonChina
  3. 3.School of Hotel and Tourism ManagementThe Hong Kong Polytechnic UniversityHung Hom, KowloonChina

Personalised recommendations