ABSTRACT
Using a large dataset of Yelp's online reviews for local businesses, we investigate how Word-of-Mouth research can inform the design of local online review systems and how these systems' data can extend our understanding of digital WOM in a local context. In this paper, we analyze how visual cues currently present in Yelp map to WOM concepts. We also show that these concepts are highly related to the perceived usefulness of the local reviews, which is aligned with prior WOM literature. Additionally, we found that local expertise, measured at the level of the neighborhood, strongly correlates with the perceived usefulness of reviews. Our findings augment the understanding of local online WOM and have design implications for local review systems.
- E. W. Anderson. Customer satisfaction and word of mouth. Journal of Service Research, 1(1):5--17, 1998.Google ScholarCross Ref
- J. Antin, M. de Sa, and E. F. Churchill. Local experts and online review sites. In CSCW, pp. 55--58, 2012. Google ScholarDigital Library
- J. Arndt. Role of product-related conversations in the diffusion of a new product. Journal of Marketing Research, 4(000003):291--291, 1967.Google ScholarCross Ref
- H. S. Bansal and P. A. Voyer. Word-of-mouth processes within a services purchase decision context. Journal of Service Research, 3(2):166--177, 2000.Google ScholarCross Ref
- B. Brown. Beyond recommendations: Local review web sites and their impact. ACM Trans. Comput.-Hum. Interact., 19(4):1--24, 2012. Google ScholarDigital Library
- J. J. Brown and P. H. Reingen. Social ties and word-of-mouth referral behavior. Journal of Consumer Research, pp. 350--362, 1987.Google ScholarCross Ref
- M. Y. Cheung, C. Luo, C. L. Sia, and H. Chen. Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. Int. Journal of Electronic Commerce, 13(4):9--38, 2009. Google ScholarDigital Library
- C. Dellarocas. The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science, 49(10):1407--1424, 2003. Google ScholarDigital Library
- W. Duan, B. Gu, and A. B. Whinston. Do online reviews matter? An empirical investigation of panel data. Decision Support Systems, 45(4):1007--1016, 2008. Google ScholarDigital Library
- D. Duhan, S. Johnson, J. Wilcox, and G. Harrell. Influences on consumer use of word-of-mouth recommendation sources. Journal of the Academy of Marketing Science, 25(4):283--295, 1997.Google ScholarCross Ref
- R. East, K. Hammond, and M. Wright. The relative incidence of positive and negative word of mouth: A multi-category study. Int. Journal of Research in Marketing, 24(2):175 -- 184, 2007.Google ScholarCross Ref
- J. E. Engel, R. D. Blackwell, and R. J. Kegerreis. How information is used to adopt an innovation. Journal of Advertising Research, 9(December):3--8, 1969.Google Scholar
- S. P. Feldman and M. C. Spencer. The effect of personal influence in the selection of consumer services, 1965.Google Scholar
- G. S. Mesch and O. Manor. Social ties, environmental perception, and local attachment. Environment and behavior, 30(4):504--519, 1998.Google ScholarCross Ref
- L. Rainie, K. Purcell, A. Mitchell, and T. Rosenstiel. Where people get information about restaurants and other local businesses. Tech. report, Pew Research Center, 2011.Google Scholar
- C. Rollero and N. De Piccoli. Place attachment, identification and environment perception: An empirical study. Journal of Environmental Psychology, 30(2):198--205, 2010.Google ScholarCross Ref
- T. Rosenstiel, A. Mitchell, K. Purcell, and L. Rainie. How people learn about their local community. Tech. report, Pew Research Center, 2011.Google Scholar
- J. C. Sweeney, G. N. Soutar, and T. Mazzarol. Factors influencing word of mouth effectiveness: receiver perspectives. European Journal of Marketing, 42(3/4):344--364, 2008.Google ScholarCross Ref
Index Terms
Analysis of local online review systems as digital word-of-mouth
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