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The impact of sharing brand messages: How message, sender and receiver characteristics influence brand attitudes and information diffusion on Social Networking Sites

Theo Araujo
From the journal Communications

Abstract

Social Networking Sites (SNSs) not only enable users to read or create content about brands, but also to easily pass along this content using information diffusion mechanisms such as retweeting or sharing. While these capabilities can be optimal for viral marketing, little is known, however, about how reading brand messages passed along by SNS contacts influences online brand communication outcomes. Results of a survey with active SNS users indicate that (1) message evaluation, (2) the relationship with the sender, and (3) the receiver’s opinion leadership and opinion-seeking levels influence not only the receiver’s intention to pass along the message further, but also his or her attitude towards the brand. The implications of these findings are discussed, including how these capabilities brought on by SNSs change the brand-consumer relationship online.

References

Amichai-Hamburger, Y., & Vinitzky, G. (2010). Social network use and personality. Computers in Human Behavior, 26(6), 1289–1295. https://doi.org/10.1016/j.chb.2010.03.018Search in Google Scholar

Amos, C., Holmes, G., & Strutton, D. (2008). Exploring the relationship between celebrity endorser effects and advertising effectiveness: A quantitative synthesis of effect size. International Journal of Advertising, 27(2), 209–234.Search in Google Scholar

Araujo, T., & Neijens, P. (2012). Friend me: Which factors influence top global brands participation in social network sites. Internet Research, 22(5), 626–640. https://doi.org/10.1108/10662241211271581Search in Google Scholar

Araujo, T., Neijens, P. C., & Vliegenthart, R. (2015). What motivates consumers to re-Tweet brand content? The impact of information, emotion, and traceability on pass-along behavior. Journal of Advertising Research, 55(3), 284–295.Search in Google Scholar

Araujo, T., Neijens, P., & Vliegenthart, R. (2017). Getting the word out on Twitter: The role of influentials, information brokers and strong ties in building word-of-mouth for brands. International Journal of Advertising, 36(3), 496–513. https://doi.org/10.1080/02650487.2016.1173765Search in Google Scholar

Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of Marketing Research, 291–295.Search in Google Scholar

Babic Rosario, A., Sotgiu, F., de Valck, K., & Bijmolt, T. H. (2016). The effect of electronic word of mouth on sales: A meta-analytic review of platform, product, and metric factors. Journal of Marketing Research, 53(3), 297–318.Search in Google Scholar

Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 644–656.Search in Google Scholar

Baker, A. M., Donthu, N., & Kumar, V. (2016). Investigating how word-of-mouth conversations about brands influence purchase and retransmission intentions. Journal of Marketing Research, 53(2), 225–239.Search in Google Scholar

Bakshy, E., Hofman, J. M., Mason, W. A., & Watts, D. J. (2011). Everyone’s an influencer: Quantifying influence on twitter. In Proceedings of the fourth ACM international conference on web search and data mining (pp. 65–74). Retrieved March 8, 2018 from http://dl.acm.org/citation.cfm?id=1935845.Search in Google Scholar

Bakshy, E., Rosenn, I., Marlow, C., & Adamic, L. A. (2012). The role of social networks in information diffusion. In Proceedings of the 21st international conference on World Wide Web (pp. 519–528). Retrieved March 8, 2018 from http://dl.acm.org/citation.cfm?id=2187907.Search in Google Scholar

Barreto, A. M. (2014). The word-of-mouth phenomenon in the social media era. International Journal of Market Research, 56(5), 631–654.Search in Google Scholar

Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192–205.Search in Google Scholar

Boyd, D., Golder, S., & Lotan, G. (2010). Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. In System Sciences (HICSS), 2010 43rd Hawaii International Conference on System Sciences (pp. 1–10).Search in Google Scholar

Bronner, F., & de Hoog, R. (2010). Vacationers and eWOM: Who posts, and why, where, and what? Journal of Travel Research, 50(1), 15–26. https://doi.org/10.1177/0047287509355324Search in Google Scholar

Brooks, R. C. (1957). “Word-of-mouth” advertising in selling new products. The Journal of Marketing, 22(2), 154–161.Search in Google Scholar

Brown, J., Broderick, A. J., & Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of Interactive Marketing, 21(3), 2–20. https://doi.org/10.1002/dir.20082Search in Google Scholar

Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer Research, 350–362.Search in Google Scholar

Burt, R. S. (2000). The network structure of social capital. Research in Organizational Behavior, 22, 345–423.Search in Google Scholar

Chiu, H. C., Hsieh, Y. C., Kao, Y. H., & Lee, M. (2007). The determinants of email receivers’ disseminating behaviors on the internet. Journal of Advertising Research, 47(4), 524–534.Search in Google Scholar

Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & van Wijk, R. (2007). Why pass on viral messages? Because they connect emotionally. Business Horizons, 50, 291–304.Search in Google Scholar

Eckler, P., & Bolls, P. (2011). Spreading the virus: Emotional tone of viral advertising and its effect on forwarding intentions and attitudes. Journal of Interactive Advertising, 11(2), 1–11.Search in Google Scholar

Feick, L. F., & Price, L. L. (1987). The market maven: A diffuser of marketplace information. The Journal of Marketing, 83–97.Search in Google Scholar

Fielding, A., & Goldstein, H. (2006). Cross-classified and multiple membership structures in multilevel models: An introduction and review. Retrieved March 8, 2018 from http://dera.ioe.ac.uk/6469/1/RR791.pdf.Search in Google Scholar

Flynn, L. R., Goldsmith, R. E., & Eastman, J. K. (1996). Opinion leaders and opinion seekers: Two new measurement scales. Journal of the Academy of Marketing Science, 24(2), 137–147.Search in Google Scholar

Gelman, A. (2008). Scaling regression inputs by dividing by two standard deviations. Statistics in Medicine, 27(15), 2865–2873. https://doi.org/10.1002/sim.3107.Search in Google Scholar

Gensler, S., Völckner, F., Liu-Thompkins, Y., & Wiertz, C. (2013). Managing brands in the social media environment. Journal of Interactive Marketing, 27(4), 242–256. https://doi.org/10.1016/j.intmar.2013.09.004Search in Google Scholar

Goldstein, H. (1994). Multilevel cross-classified models. Sociological Methods & Research, 22(3), 364–375.Search in Google Scholar

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 1360–1380.Search in Google Scholar

Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, 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. https://doi.org/10.1002/dir.10073Search in Google Scholar

Hollenbaugh, E. E., & Ferris, A. L. (2014). Facebook self-disclosure: Examining the role of traits, social cohesion, and motives. Computers in Human Behavior, 30, 50–58. https://doi.org/10.1016/j.chb.2013.07.055Search in Google Scholar

Huang, C.-C., Lin, T.-C., & Lin, K.-J. (2009). Factors affecting pass-along email intentions (PAEIs): Integrating the social capital and social cognition theories. Electronic Commerce Research and Applications, 8, 160–169.Search in Google Scholar

Hutton, G., & Fosdick, M. (2011). The globalization of social media: Consumer relationships with brands evolve in the digital space. Journal of Advertising Research, 51(4).Search in Google Scholar

Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology, 60(11), 2169–2188. https://doi.org/10.1002/asi.21149Search in Google Scholar

Jin, S.-A. A., & Phua, J. (2014). Following celebrities’ tweets about brands: The impact of twitter-based electronic word-of-mouth on consumers’ source credibility perception, buying intention, and social identification with celebrities. Journal of Advertising, 43(2), 181–195. https://doi.org/10.1080/00913367.2013.827606Search in Google Scholar

Katz, E. (1957). The two-step flow of communication: An up-to-date report on an hypothesis. The Public Opinion Quarterly, 21(1), 61–78.Search in Google Scholar

Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57(1), 1–22.Search in Google Scholar

Kim, E., Sung, Y., & Kang, H. (2014). Brand followers’ retweeting behavior on Twitter: How brand relationships influence brand electronic word-of-mouth. Computers in Human Behavior, 37, 18–25. https://doi.org/10.1016/j.chb.2014.04.020Search in Google Scholar

Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York, NY: Guilford Press.Search in Google Scholar

Knoll, J., & Schramm, H. (2015). Advertising in social network sites – Investigating the social influence of user generated content on online advertising effects. Communications: The European Journal of Communication Research, 40(3), 341–360. https://doi.org/10.1515/commun-2015-0011Search in Google Scholar

Kozinets, R. V., De Valck, K., Wojnicki, A. C., & Wilner, S. J. (2010). Networked narratives: Understanding word-of-mouth marketing in online communities. Journal of Marketing, 74(2), 71–89.Search in Google Scholar

Kwon, E. S., & Sung, Y. (2011). Follow me! Global marketers’ twitter use. Journal of Interactive Advertising, 12(1), 4–16.Search in Google Scholar

Liu, Z., Liu, L., & Li, H. (2012). Determinants of information retweeting in microblogging. Internet Research, 22(4), 443–466.Search in Google Scholar

Lyons, B., & Henderson, K. (2005). Opinion leadership in a computer-mediated environment. Journal of Consumer Behaviour, 4(5), 319–329.Search in Google Scholar

MacKenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator of advertising effectiveness: A test of competing explanations. Journal of Marketing Research, 23(2), 130–143. https://doi.org/10.2307/3151660Search in Google Scholar

MacInnis, D. J., & Jaworski, B. J. (1989). Information processing from advertisements: toward an integrative framework. Journal of Marketing, 53(4), 1–23. https://doi.org/10.2307/1251376Search in Google Scholar

Marwick, A., & Boyd, D. (2011). To see and be seen: Celebrity practice on Twitter. Convergence: The International Journal of Research into New Media Technologies, 17(2), 139–158. https://doi.org/10.1177/1354856510394539Search in Google Scholar

Mikalef, P., Pateli, A., & Giannakos, M. (2013). Why are users of Social Media inclined to word-of-mouth? In Collaborative, Trusted and Privacy-Aware e/m-Services (pp. 112–123). Springer. Retrieved March 8, 2018 from http://link.springer.com/chapter/10.1007/978-3-642-37437-1_10.Search in Google Scholar

Muntinga, D. G., Moorman, M., & Smit, E. G. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30(1), 13–46. https://doi.org/10.2501/IJA-30-1-013-046Search in Google Scholar

Myers, J. H., & Robertson, T. S. (1972). Dimensions of opinion leadership. Journal of Marketing Research, 41–46.Search in Google Scholar

Nagy, J., & Midha, A. (2014). The value of earned audiences: How social interactions amplify TV impact: What programmers and advertisers can gain from earned social impressions. Journal of Advertising Research, 54(4), 448–453.Search in Google Scholar

Nielsen (2012). State of the media: The Social Media Report 2012. Retrieved March 8, 2018 from http://www.nielsen.com/us/en/insights/reports-downloads/2012/state-of-the-media-the-social-media-report-2012.html.Search in Google Scholar

Okazaki, S. (2008). Determinant factors of mobile-based word-of-mouth campaign referral among Japanese adolescents. Psychology and Marketing, 25(8), 714–731. https://doi.org/10.1002/mar.20235Search in Google Scholar

Okazaki, S. (2009). Social influence model and electronic word of mouth: PC versus mobile internet. International Journal of Advertising, 28(3), 439–472. https://doi.org/10.2501/S0265048709200692Search in Google Scholar

Okazaki, S., & Yagüe, M. J. (2012). Responses to an advergaming campaign on a mobile social networking site: An initial research report. Computers in Human Behavior, 28(1), 78–86. https://doi.org/10.1016/j.chb.2011.08.013Search in Google Scholar

Petrovic, S., Osborne, M., & Lavrenko, V. (2011). RT to Win! Predicting message propagation in Twitter. Artificial Intelligence, 586–589.Search in Google Scholar

Phelps, J., 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(4), 333–348.Search in Google Scholar

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(2), 30–38.Search in Google Scholar

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.Search in Google Scholar

Schivinski, B., Christodoulides, G., & Dabrowski, D. (2016). Measuring consumers’ engagement with brand-related social-media content. Journal of Advertising Research, JAR-2016-004. https://doi.org/10.2501/JAR-2016-004Search in Google Scholar

Sengupta, J., & Johar, G. V. (2002). Effects of inconsistent attribute information on the predictive value of product attitudes: Toward a resolution of opposing perspectives. Journal of Consumer Research, 29(1), 39–56. https://doi.org/10.1086/339920Search in Google Scholar

Suh, B., Hong, L., Pirolli, P., & Chi, E. H. (2010). Want to be retweeted? Large scale analytics on factors impacting retweet in Twitter network. In Proceedings of the International Conference on Social Computing.Search in Google Scholar

Sun, T., Youn, S., Wu, G., & Kuntaraporn, M. (2006). Online word-of-mouth (or mouse): An exploration of its antecedents and consequences. Journal of Computer-Mediated Communication, 11(4), 1104–1127.Search in Google Scholar

Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site. Journal of Marketing, 73(5), 90–102.Search in Google Scholar

van Noort, G., Antheunis, M. L., & van Reijmersdal, E. A. (2012). Social connections and the persuasiveness of viral campaigns in social network sites: Persuasive intent as the underlying mechanism. Journal of Marketing Communications, 18(1), 39–53. https://doi.org/10.1080/13527266.2011.620764Search in Google Scholar

van Noort, G., & Willemsen, L. M. (2012). Online damage control: The effects of proactive versus reactive webcare interventions in consumer-generated and brand-generated platforms. Journal of Interactive Marketing, 26(3), 131–140. https://doi.org/10.1016/j.intmar.2011.07.001Search in Google Scholar

Voss, K. E., Spangenberg, E. R., & Grohmann, B. (2003). Measuring the hedonic and utilitarian dimensions of consumer attitude. Journal of Marketing Research, 40(3), 310–320.Search in Google Scholar

Willemsen, L. M., Neijens, P. C., Bronner, F., & de Ridder, J. A. (2011). “Highly recommended!” The content characteristics and perceived usefulness of online consumer reviews. Journal of Computer-Mediated Communication, 17(1), 19–38.Search in Google Scholar

Published Online: 2019-06-08
Published in Print: 2019-06-07

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