Association between Web Semantics and Geographical Locations: Evaluate Internet Information Consistency for Marketing Research

Social software completely revolutionizes the way of information sharing by allowing every individual to read, share and publish online. In terms of marketing, it is an effective way to understand consumers’ perceptions and beliefs in different local regions by analyzing and comparing the web content regarding a specific product retrieved on the Internet with respect to different locations. Interestingly, incidents originated from a location may attract more Internet discussions by individuals from remote locations. Therefore, it is difficult to measure the strength of people’s perceptions between different locations if we solely rely on the web traffic statistics. Moreover, it is difficult to compare strength of perceptions retrieved by different search engines, at different times, and on different topics. To overcome these inadequacies, the authors introduce a quantitative metric, Perceived Index on Information (PI), to measure the strength of web content over different search engines, different time intervals, and different topics with respect to geographical locations. Further visualizing PI in maps provides an instant and low-cost mean for word-of-mouth analysis that brings competitive advantages in business marketing.

[1]  Andy Sernovitz,et al.  Word of Mouth Marketing: How Smart Companies Get People Talking , 2006 .

[2]  W. Chismar,et al.  The interaction of institutionally triggered and technology-triggered social structure change: an investigation of computerized physician order entry , 2007 .

[3]  Carolyn Watters,et al.  A field study characterizing Web-based information-seeking tasks , 2007 .

[4]  Chrysanthos Dellarocas,et al.  The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms , 2003, Manag. Sci..

[5]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[6]  L. Chernatony,et al.  Corporate marketing and service brands ‐ Moving beyond the fast‐moving consumer goods model , 2001 .

[7]  Judit Bar-Ilan,et al.  User rankings of search engine results , 2007, J. Assoc. Inf. Sci. Technol..

[8]  Alice M. Tybout,et al.  Using Information Processing Theory to Design Marketing Strategies , 1981 .

[9]  Amanda Spink,et al.  Web Search: Public Searching of the Web , 2011, Information Science and Knowledge Management.

[10]  Scott Nicholson,et al.  How much of it is real? Analysis of paid placement in Web search engine results , 2006 .

[11]  Cate Riegner Word of Mouth on the Web: The Impact of Web 2.0 on Consumer Purchase Decisions , 2007, Journal of Advertising Research.

[12]  Jerri L. Ledford,et al.  Google Analytics , 2006 .

[13]  Samer Faraj,et al.  Why Should I Share? Examining Social Capital and Knowledge Contribution in Electronic Networks of Practice , 2005, MIS Q..

[14]  Peter M. Clarkson,et al.  Market Reaction to Takeover Rumour in Internet Discussion Sites , 2006 .

[15]  Brant Barton Ratings, Reviews & ROI , 2006 .

[16]  Michael J. Shaw,et al.  Buyers' Choice of Online Search Strategy and Its Managerial Implications , 2006, J. Manag. Inf. Syst..

[17]  Michael A. Kamins,et al.  Consumer Responses to Rumors: Good News, Bad News , 1997 .

[18]  Dennis L. Hoffman,et al.  Marketing in Hypermedia Computer-Mediated Environments : Conceptual Foundations 1 ) , 1998 .

[19]  Wai Lam,et al.  Introduction to the special topic section on mining Web resources for enhancing information retrieval , 2007, J. Assoc. Inf. Sci. Technol..

[20]  Michael A. Shepherd,et al.  A Field Study Characterizing Web-based Information Seeking Tasks , 2022 .

[21]  Robert W. Zmud,et al.  Behavioral Intention Formation in Knowledge Sharing: Examining the Roles of Extrinsic Motivators, Social-Psychological Factors, and Organizational Climate , 2005, MIS Q..

[22]  Cecil Eng Huang Chua,et al.  The Role of Online Trading Communities in Managing Internet Auction Fraud , 2007, MIS Q..

[23]  Kirthi Kalyanam,et al.  Adaptive experimentation in interactive marketing: The case of viral marketing at Plaxo , 2007 .

[24]  Ravi Sen,et al.  Optimal Search Engine Marketing Strategy , 2005, Int. J. Electron. Commer..

[25]  Barry J. Babin,et al.  An Empirical Investigation of the Impact of Negative Public Publicity on Consumer Attitudes and Intentions , 1991 .

[26]  Hsin-Hsi Chen,et al.  Mining opinions from the Web: Beyond relevance retrieval , 2007 .

[27]  James A. Hendler,et al.  A new journal for a new era of the World Wide Web , 2003, J. Web Semant..

[28]  Barry Berman,et al.  Data mining: On the trail to marketing gold , 2004 .

[29]  R. Brooks,et al.  “Word-of-Mouth” Advertising in Selling New Products , 1957 .

[30]  Xueming Luo,et al.  Consumer Negative Voice and Firm-Idiosyncratic Stock Returns , 2007 .

[31]  Riadh Ladhari,et al.  The effect of consumption emotions on satisfaction and word‐of‐mouth communications , 2007 .

[32]  R. Olshavsky,et al.  The dual role of informational social influence: Implications for marketing management , 1987 .

[33]  Allan J. Kimmel Rumors and the Financial Marketplace , 2004 .

[34]  M. Cooke,et al.  Web 2.0, Social Networks and the Future of Market Research , 2008 .

[35]  Joseph Heinen,et al.  Internet marketing practices , 1996, Inf. Manag. Comput. Secur..

[36]  Joel B. Cohen,et al.  Informational Social Influence and Product Evaluation. , 1972 .

[37]  Karl Reiner Lang,et al.  Do Search Terms Matter for Online Consumers? The Interplay Between Search Engine Query Specification and Topical Organization , 2007, Decis. Support Syst..