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Twitter power: Tweets as electronic word of mouth

  1. Bernard J. Jansen1,
  2. Mimi Zhang1,
  3. Kate Sobel2,
  4. Abdur Chowdury3

Article first published online: 6 JUL 2009

DOI: 10.1002/asi.21149

Issue

Journal of the American Society for Information Science and Technology

Journal of the American Society for Information Science and Technology

Volume 60, Issue 11, pages 2169–2188, November 2009

Additional Information

How to Cite

Jansen, B. J., Zhang, M., Sobel, K. and Chowdury, A. (2009), Twitter power: Tweets as electronic word of mouth. J. Am. Soc. Inf. Sci., 60: 2169–2188. doi: 10.1002/asi.21149

Author Information

  1. 1

    College of Information Sciences and Technology, Pennsylvania State University, University Park, PA 18802

  2. 2

    Smeal College of Business Administration, Pennsylvania State University, University Park, PA 18802

  3. 3

    Twitter, Inc., San Francisco, CA 94107

Publication History

  1. Issue published online: 6 OCT 2009
  2. Article first published online: 6 JUL 2009
  3. Manuscript Accepted: 11 MAY 2009
  4. Manuscript Revised: 7 MAY 2009
  5. Manuscript Received: 28 FEB 2009

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References

  • Allen, J., & Perrault, C.R. (1986). Analyzing intention in utterances. In B.J.Grosz, K.Sparck-Jones, & B.L.Webber (Eds.), Readings in natural language processing (pp. 441–458). San Francisco: Morgan Kaufmann.
  • Anderson, E.W. (1998). Customer satisfaction and word of mouth. Journal of Service Research, 1(1), 5–17.
  • Archak, N., Ghose, A., & Ipeirotis, P.G. (2007, 12–15 August). In R.Caruana & X.Wu (Eds.), Show me the money! Deriving the pricing power of product features by mining consumer reviews (pp. 56–66). Paper presented at the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '07). New York: ACM Press.
  • Barton, B. (2006). Ratings, reviews & ROI: How leading retailers use customer word of mouth in marketing and merchandising. Journal of Advertising Research, 7, article 87.
  • Bausch, S., & McGiboney, M. (2008). Nielsen online provides fastest growing social networks for September 2008. New York: Nielsen Company.
  • Benedicktus, R.L., & Andrews, M.L. (2006). Building trust with consensus information: The effects of valence and sequence direction. Journal of Interactive Advertising, 6. Retrieved June 12, 2009, from http://www.jiad.org/article77
  • Broder, A. (2002). A taxonomy of Web search. SIGIR Forum, 36(2), 3–10.
  • Brogan, C. (2008). Fifty ways to use Twitter for business. Retrieved February 21, 2009, from http://socialcomputingmagazine.com/viewcolumn.cfm?colid=592
  • Brown, T.J., Barry, T.E., Dacin, P.A., & Gunst, R.F. (2005). Spreading the word: Investigating antecedents of consumers' positive word-of-mouth intentions and behaviors in a retailing context. Journal of the Academy of Marketing Science, 33(2), 123–138.
  • Cheung, C.M.K., Lee, M.K.O., & Rabjohn, N. (2008). The impact of electronic word-of-mouth. The adoption of online opinions in online customer communities. Internet Research, 18(3), 229–247.
  • Church, K.W., & Hanks, P. (1990). Word association norms, mutual information, and lexicography. Computational Linguistics, 16(1), 22–29.
  • Conrad, J.G., Leidner, J.L., & Schilder, F. (2008, 30 October). In J.G.J.Shanahan (Ed.), Professional credibility: Authority on the Web. Paper presented at the Second ACM Workshop on Information Credibility on the Web (WICOW '08) (pp. 85–88). New York: ACM Press.
  • Davenport, T.H., & Beck, J.C. (2002). The attention economy: Understanding the new currency of business. Cambridge, MA: Harvard Business Press.
  • Davis, A., & Khazanchi, D. (2008). An empirical study of online word of mouth as a predictor for multi-product category e-Commerce sales. Electronic Markets, 18(2), 130–141.
  • Dellarocas, C. (2003). The digitization of word-of-mouth: Promise and challenges of online reputation systems. Management Science, 49(10), 1407–1424.
  • Dobson, A.J. (2002). An introduction to generalized linear models. New York: CRC Press.
  • Duana, W., Gub, B., & Whinston, A.B. (2008). Do online reviews matter?—An empirical investigation of panel data. Decision Support Systems, 45(3), 1007–1016.
  • Ebner, M., & Schiefner, M. (2008). In Microblogging—more than fun? In I.Arnedillo Sánchez & P.Isaías (Eds.), Proceedings of the IADIS Mobile Learning Conference (pp. 155–159). Lisbon, Portugal: IADIA.
  • Engel, J.E., Blackwell, R.D., & Kegerreis, R.J. (1969). How information is used to adopt an innovation. Journal of Advertising Research, 9(December), 3–8.
  • Ennew, C.T., Banerjee, A.K., & Li, D. (2000). Managing word of mouth communication: Empirical evidence from India. International Journal of Bank Marketing, 18(2), 75–83.
  • Esch, F.-R., Langner, T., Schmitt, B.H., & Geus, P. (2006). Are brands forever? How brand knowledge and relationships affect current and future purchases. Journal of Product & Brand Management, 15(2), 98–105.
  • Fehr, E., & Falk, A. (2002). Psychological foundations of incentives. European Economic Review, 46(4), 687–724.
  • Gelb, B.D., & Sundaram, S. (2002). Adapting to ‘word of mouse.’ Business Horizons, 45(4), 21–25.
  • Glaser, B., & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. Chicago: Aldine.
  • Goldman, E. (2008). Online word of mouth and its implications for trademark law. In G.B.Dinwoodie & M.D.Janis (Eds.), Trademark law and theory a handbook of contemporary research (pp. 404–429). Cheltenham, UK: Edward Elgar.
  • Goldsmith, R.E., & Horowitz, D. (2006). Measuring motivations for online opinion seeking. Journal of Interactive Advertising 6. Retrieved June 10, 2009, from http://www.jiad.org/article76
  • Grice, H. (1969). Utterers meaning and intentions. Philosophical Review, 78(2), 47–177.
  • Grosseck, G., & Holotesch, C. (2008, April). Can we use Twitter for educational activities? Paper presented at the Fourth International Scientific Conference eLearning and Software for Education, Bucharest, Romania.
  • Ha, H.-Y. (2006). The effects of consumer risk perception on pre-purchase information in online auctions: Brand, word-of-mouth, and customized information. Journal of Computer-Mediated Communication, 8, article 2.
  • Helps, J.E., Lewis, R., Mobilio, L., Perry, D., & Raman, N. (2004). Viral marketing or electronic word-of-mouth advertising: Examining consumer responses and motivations to pass along email. Journal of Advertising Research, 44(2), 333–348.
  • Hennig-Thurau, T., Gwinner, K.P., Walsh, G., & Gremle, D.D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing, 18(1), 38–52.
    Direct Link:
  • Huberman, B.A., Romero, D.M., & Wu, F. (2009). Social networks that matter: Twitter under the microscope. First Monday 14, (1–5).
  • Jansen, B.J., Booth, D., & Spink, A. (2008). Determining the informational, navigational, and transactional intent of Web queries. Information Processing & Management, 44(3), 1251–1266.
  • Jansen, B.J., & Spink, A. (2005). How are we searching the World Wide Web? A comparison of nine search engine transaction logs. Information Processing & Management, 42(1), 248–263.
  • Java, A., Song, X., Finin, T., & Tseng, B. (2007). Why we Twitter: Understanding microblogging usage and communities. In H.Zhang, B.Mobasher, C.L.Giles, A.McCallum, O.Nasraoui, M.Spiliopoulou, J.Srivastava, & J.Yen (Eds.), Proceedings of the Ninth WebKDD and First SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis (WebKDD/SNA-KDD '07) (pp. 56–65). New York: ACM Press.
  • Jung, C.G. (1959). A visionary rumor. Journal of Applied Psychology, 4, 5–19.
  • Katz, E., & Lazarsfeld, P.F. (1955). Personal influence: The part played by people in the flow of mass communication. New York: Free Press.
  • Kiecker, P., & Cowles, D.L. (2001). Interpersonal communication and personal influence on the Internet: A framework for examining online word-of-mouth. Journal of Euromarketing, 11(2), 71–88.
  • Kimmel, A.J. (2004). Rumors and rumor control: A manager's guide to understanding and combatting rumors. Mahwah, NJ: Lawrence Erlbaum.
  • Lee, D., Jeong, O.-R., & Lee, S.-G. (2008). Opinion mining of customer feedback data on the Web. In W.Kim & H.J.Choi (Eds.), Proceedings of the Second International Conference on Ubiquitous Information Management and Communication (pp. 230–235). New York: ACM Press.
  • Liu, B., Hu, M., & Cheng, J. (2005). Opinion observer: Analyzing and comparing opinions on the Web. In A.Ellis & T.Hagino (Chairs), Proceedings of the 14th International Conference on World Wide Web (WWW '05) (pp. 342–351). New York: ACM Press.
  • McFedries, P. (2007). Technically speaking: All a-Twitter. IEEE Spectrum, 44(10), 84.
  • McGraw Hill Higher Education. (n.d.). Starbucks case study. Retrieved February 16, 2009, from http://www.mhhe.com/business/management/thompson/11e/case/starbucks.html
  • Milstein, S., Chowdhury, A., Hochmuth, G., Lorica, B., & Magoulas, R. (2008). Twitter and the micro-messaging revolution: Communication, connections, and immediacy—140 characters at a time. Sebastopol, CA: O'Reilly Media.
  • Montoya-Weiss, M.M., Voss, G.B., & Grewal, D. (2003). Determinants of online channel use and overall satisfaction with a relational, multichannel service provider. Journal of the Academy of Marketing Science, 31(4), 448–458.
  • Muniz, A.M.J., & O'Guinn, T.C. (2001). Brand community. Journal of Consumer Research, 27(4), 412–432.
  • Nardi, B.A., Schiano, D.J., Gumbrecht, M., & Swartz, L. (2004). Why we blog. Communications of the ACM, 47(12), 41–46.
  • Panzarasa, P., Opsahl, T., & Carley, K.M. (2009). Patterns and dynamics of users' behavior and interaction: Network analysis of an online community. Journal of the American Society for Information Science and Technology, 60(5), 911–932.
    Direct Link:
  • Park, C., & Lee, T.M. (2009). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of Business Research, 62(1), 61–67.
  • Patton, M.Q. (1990). Qualitative evaluation and research methods (2d ed.). Newbury Park, CA: Sage Publications.
  • Porter, L., & Golan, G.J. (2006). From subservient chickens to brawny men: A comparison of viral advertising to television advertising. Journal of Interactive Advertising, 6. Retrieved June 12, 2009, from http://www.jiad.org/article78.
  • Postman, J. (2008). Seven rules for establishing a corporate presence on Twitter. Retrieved February 27, 2009, from http://www.socialmedia today.com/SMC/44452
  • Rafaeli, S., Ravid, G., & Soroka, V. (2004). De-lurking in virtual communities: A social communication network approach to measuring the effects of social and cultural capital. In R.H.Sprague (Chair), Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS 04) (p. 10). Los Alamitos, CA: IEEE.
  • Reinartz, W., Krafft, M., & Hoyer, W.D. (2004). The customer relationship management process: Its measurement and impact on performance. Journal of Marketing Research, 41(3), 293–305.
  • Reynolds, G. (2006). An army of Davids: How markets and technology empower ordinary people to beat big media, big government, and other Goliaths. Nashville, TN: Thomas Nelson.
  • Richins, M.L. (1983). Negative word-of mouth by dissatisfied consumers: A pilot study. Journal of Marketing, 47(Winter), 68–78.
  • Richins, M.L. (1984). Word-of-mouth communication as negative information. Advances in Consumer Research, 44, 697–702.
  • Richins, M.L., & Root-Shaffer, T. (1988). The role of involvement and opinion leadership in consumer word-of-mouth: An implicit model made explicit. Advances in Consumer Research, 15, 32–36.
  • Rose, D.E., & Levinson, D. (2004). Understanding user goals in Web search. In S.Feldman & M.Uretsky (Eds.), Proceedings of the 13th International Conference on World Wide Web (WWW '04) (pp. 13–19). New York: ACM Press.
  • Skowronski, J.J., & Carlston, D.E. (1989). Negativity and extremity in impression formation: A review of explanations. Psychology Bulletin, 105(January), 131–142.
  • Starbucks. (2008). Company fact sheet. Retrieved February 16, 2009, from http://www.starbucks.com/aboutus/Company_Factsheet.pdf
  • Sundar, S.S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In M.J.Metzger & A.J.Flanagin (Eds.), Digital media, youth, and credibility (pp. 73–100). Cambridge, MA: MIT Press.
  • Thompson, C. (2008, 5 September). Brave new world of digital intimacy. Retrieved June 12, 2009, from http://www.nytimes.com/2008/09/07/magazine/07awareness-t.html?_r=1
  • Thorson, K.S., & Rodgers, S. (2006). Relationships between blogs as eWOM and interactivity, perceived interactivity, and parasocial interaction. Journal of Interactive Advertising, 6. Retrieved June 12, 2009, from http://www.jiad.org/article79
  • Urban, G. (2005). Don't just relate—advocate: A blueprint for profit in the era of customer power. Upper Saddle River, NJ: Wharton School Publishing.
  • Wang, P., Berry, M., & Yang, Y. (2003). Mining longitudinal Web queries: Trends and patterns. Journal of the American Society for Information Science and Technology, 54(8), 743–758.
    Direct Link:
  • Wells, W., Moriarty, S., & Burnett, J. (2000). Advertising principles and practice. Upper Saddle River, NJ: Prentice Hall.
  • Wijaya, D.T., & Bressan, S. (2008). A random walk on the red carpet: Rating movies with user reviews and Page Rank. In J.G.Shanahan (Ed.), Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM '08) (pp. 951–960). New York: ACM Press.
  • Wikipedia. (2009). Starbucks. Retrieved February 16, 2009, from http://en.wikipedia.org/wiki/Starbucks
  • Zhang, M., & Jansen, B.J. (2008). Using action-object pairs as a conceptual framework for transaction log analysis. In B.J.Jansen, A.Spink & I.Taksa (Eds.), Handbook of research on Web log analysis (pp. 414–433). Hershey, PA: IGI.
  • Zhang, W., Yu, C., & Meng, W. (2007). Opinion retrieval from blogs. In M.J.Silva, A.A.F.Laender, R.Baeza-Yates, D.L.McGuinness, B.Olstad, O.H.Olsen & A.O.Ealcao (Eds.), Proceedings of the 16th ACM Conference on Conference on Information and Knowledge Management (CIKM '07) (pp. 831–841). New York: ACM Press.
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