Selective Electronic Word-of-Mouth

The Roles of Issue Controversiality and Issue Involvement



eWOM, issue controversiality, issue involvement, source cue, cause-related marketing


Electronic word-of-mouth (eWOM) is associated with “going viral” that communicators strive for when designing their messaging strategies. These referrals could increase brand awareness, brand loyalty, and purchase intentions. The study focuses on cause-related marketing (CRM) strategies by exploring the effects of social issue controversiality (highly controversial issues vs. moderately controversial issues) on selective Electronic Word-of-Mouth (eWOM) by considering source cues and issue involvement. The researchers conducted a two-wave survey experiment to explore the research topic. The findings suggest individuals’ decisions to eWOM depend on issue types and issue involvement. Social media users are motivated to share CRM featuring moderately-controversial issues rather than highly-controversial issues to a wider audience on Facebook. People who perceive the issue information with more personal involvement are more likely to share highly-controversial issues with their close friends. There is no source cue effect. The theoretical and practical contribution were discussed.

Author Biographies

Nicky Chang Bi, University of Nebraska at Omaha

Assistant professor, School of Communication

Yanqin Lu, Bowling Green State University

Associate Professor, School of Media and Communication


Aaker, Jennifer, Kathleen D. Vohs, and Cassie Mogilner (2010), "Nonprofits Are Seen as Warm and For-profits as Competent: Firm Stereotypes Matter," Journal of Consumer Research, 37 (2), 224-237.

Anheier, H. (2013, Spring). The nonprofits of 2025. Stanford Social Innovation Review.

Arlt, D., Dalmus, C., & Metag, J. (2019). Direct and indirect effects of involvement on hostile media perceptions in the context of the refugee crisis in Germany and Switzerland. Mass Communication and Society, 22(2), 171-195.

Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of marketing Research, 4(3), 291-295.

Bi, C., Zhang, R., & Ha, L. (2018). Does valence of product review matter? The mediating role of self effects and third-person effects in sharing YouTube word-of-mouth (vWOM). Journal of Research in Interactive Marketing. doi: 10.1108/JRIM-04-2018-0049

Berinsky, A. J., Huber, G. A., & Lenz, G. S. (2012). Evaluating online labor markets for experimental research:'s Mechanical Turk. Political Analysis, 20(3), 351-368. doi: 10.1093/pan/mpr057

Bobkowski, P. S. (2015). Sharing the news: Effects of informational utility and opinion leadership on online news sharing. Journalism & Mass Communication Quarterly, 92(2), 320-345. doi: 10.1177/1077699015573194

British Library. (2013, March 8). Myths and controversies surrounding feminism, Retrieved Feberary 20, from

Bullingham, L., & Vasconcelos, A. C. (2013). ‘The presentation of self in the online world’: Goffman and the study of online identities. Journal of Information Science, 39(1), 101-112. doi: 10.1177/0165551512470051

Cambridge Dictionary. (2019). Retreived March 4, 2019 from

Chen, H. T. (2012). Multiple issue publics in the high-choice media environment: Media use, online activity, and political knowledge. Asian Journal of Communication, 22(6), 621-641.

Chia, S. C., & Tu, C. (2020). Screw the majority?: Examining partisans’ outspokenness on social networking sites. Journal of Information Technology & Politics. Advanced Online publication.

Cohen, D. (2018, January 16). The ad community’s reaction to Facebook’s news feed algorithm change experts examine how the platform's announcement affects the industry. Adweek, Retrieved December 12, 2018 from

Das, N., Guha, A., Biswas, A., & Krishnan, B. (2016). How Product–cause Fit and Donation Quantifier Interact in Cause-related Marketing (CRM) Settings: Evidence of The Cue Congruency Effect. Marketing Letters, 27 (2), 295-308.

Foster, S. J. (2006). Whose history? Portrayal of immigrant groups in U.S. history textbooks, 1800-present. In S. J. Foster & K. A. Crawford (Eds.), What shall we tell the children? International perspectives on school history textbooks (pp. 155-178). Greenwich, CT: Information Age Publishing.

Fox, J., & Holt, L. F. (2018). Fear of isolation and perceived affordances: the spiral of silence on social networking sites regarding police discrimination. Mass Communication and Society, 21(5), 533-554.

Gearhart, S., & Zhang, W. (2018). Same spiral, different day? Testing the spiral of silence across issue types. Communication Research, 45(1), 34-54.

Gleit, N. (2017, December 5). Facebook's 2017 year in review. Retrieved March 17, 2018, from

Goffman, E. (1959). The Presentation of Self in Everyday Life. NY, New York: Anchor Books.

Google (2021). Google Trends. Retrieved March 17, 2018 from

Gulati, M. (2018, February 22). 6 best award winning social media campaigns to watch in 2018. Retrieved March 17, 2018, from

Gunther, A. C., & Christen, C. T. (2002). Projection or persuasive press? Contrary effects of personal opinion and perceived news coverage on estimates of public opinion. Journal of Communication, 52(1), 177-195.

Guo, L., Su, C., & Lee, H. (2019). Effects of issue involvement, news attention, perceived knowledge, and perceived influence of anti-corruption news on Chinese students’ political participation. Journalism & Mass Communication Quarterly, 96(2), 452-472.

Harris Poll. (2006). Online survey. Reviewed from Allsop, D.T., Bassett, B.R. and Hoskins, J.A. (2007), “Word-of-mouth research: principles and applications”, Journal of Advertising Research, 47(4), 398-411.

Hayes, A. F. (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A regression-based Approach. New York, NY: Guilford Press.

Heatherly, K. A., Lu, Y., & Lee, J. K. (2017). Filtering out the other side? Cross-cutting and like-minded discussions on social networking sites. New Media & Society, 19(8), 1271-1289.

Henderson, K. (2015). Trust and source credibility in consumer engagement: a fashion blog perspective. (Master’s thesis). Retrieved from UC Research Repository.

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.

Hu, X., and Ha, L. 2015. “Which form of word-of-mouth is more important to online shoppers? A comparative study of WOM use between general population and college students.” Journal of Communication and Media Research, 7(2), 15-35.

Ismagilova, E., Slade, E., Rana, N. P., & Dwivedi, Y. K. (2019). The effect of characteristics of source credibility on consumer behaviour: A meta-analysis. Journal of Retailing and Consumer Services.

Just Captital. (2021). JUST Capital’s 2021 Americans’ views on business survey. Retrieved from

Kairam, S., Brzozowski, M., Huffaker, D. and Chi, E. (2012). Talking in circles: selective sharing in Google+. Proc. of CHI’12, 1065–1074. Retrieved from

Kees, J., Berry, C., Burton, S., & Sheehan, K. (2017). An analysis of data quality: Professional panels, student subject pools, and Amazon’s Mechanical Turk. Journal of Advertising, 46(1), 141–155. doi:10.1080/00913367.2016.1269304

Kietzmann, J., & Canhoto, A. (2013). Bittersweet! Understanding and managing electronic word of mouth. Journal of Public Affairs, 13(2), 146–159. doi:10.1002/pa.1470

Kim, E. M., & Ihm, J. (2020). More than virality: Online sharing of controversial news with activated audience. Journalism & Mass Communication Quarterly, 97(1), 118-140.

Kim, E. M., Ihm, J., & Park, H. A. (2017). News sharing as relational communication: Focusing on self-presentation tendency and characteristics of sharing audiences. Korean Journal of Broadcasting and Telecommunication Studies, 31(3), 114-151. doi: 10.1177/1461444818772847

Kim, C., & Lee, J. K. (2016). Social media type matters: investigating the relationship between motivation and online social network heterogeneity. Journal of Broadcasting & Electronic Media, 60(4), 676-693. doi: 10.1080/08838151.2016.1234481

Kim, J., Wyatt, R. O., & Katz, E. (1999). News, talk, opinion, participation: The part played by conversation in deliberative democracy. Political Communication, 16, 361-385.

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.

Krosnick, J. A. (1990). Government policy and citizen passion: A study of issue publics in contemporary America. Political Behavior, 12(1), 59-92.

Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behavior, 28, 331–339. doi: 10.1016/j.chb.2011.10.002

Lee, M. (2018, January 25). Top 10 influential social media marketing campaigns of 2017. Retrieved February 25 from

Lin, C. A., Crowe, J., Pierre, L., & Lee, Y. (2021). Effects of parasocial interaction with an instafamous influencer on brand attitudes and purchase intentions. The Journal of Social Media in Society, 10(1), 55-78.

Litt, E. (2012). Knock, knock. Who's there? The imagined audience. Journal of Broadcasting & Electronic Media, 56(3), 330-345. doi: 10.1080/08838151.2012.705195

Litt, E., & Hargittai, E. (2016). The imagined audience on social network sites. Social Media+ Society, 2(1), 1-3.

Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29(3), 458-468.

Lo, V. H., Wei, R., & Lu, H. Y. (2017). Issue importance, third-person effects of protest news, and participation in Taiwan’s sunflower movement. Journalism & Mass Communication Quarterly, 94(3), 682-702.

Lo, V. H., Wei, R., Lu, H. Y., & Hou, H. Y. (2015). Perceived issue importance, information-processing and third-person effects of news about imported U.S. beef controversality. International Journal of Public Opinion Research, 27, 341-360. doi:10.1093/ijpor/edu039

Lookadoo, K. L., & Wong, N. C. (2019). “Hey guys, check this out!# ad” The Impact of Media Figure-User Relationships and Ad Explicitness on Celebrity Endorsements. The Journal of Social Media in Society, 8(1), 178-210.

Lu, Y. (2019). Incidental exposure to political disagreement on Facebook and corrective participation: Unraveling the effects of emotional responses and issue relevance. International Journal of Communication, 13, 874-896.

Matthes, J., & Beyer, A. (2017). Toward a cognitive-affective process model of hostile media perceptions: A multi-country structural equation modeling approach. Communication Research, 44(8), 1075-1098.

Mendini, Monica, Paula C. Peter, and Michael Gibbert (2018), "The Dual-Process Model of Similarity in Cause-related Marketing: How Taxonomic Versus Thematic Partnerships Reduce Skepticism and Increase Purchase Willingness," Journal of Business Research, 91, 195-204.

Mutz, D. C. (1989). The influence of perceptions of media influence: Third person effects and the public expression of opinions. International Journal of Public Opinion Research, 1, 3-23.

Park, D., Lee, J., & Han, I. (2007). The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125–148.

Petty, R. E., & Cacioppo, J. T. (1979). Issue-involvement can increase or decrease persuasion by enhancing message-relevant cognitive responses. Journal of Personality and Social Psychology, 37, 1915-1926. doi: 10.1037/0022-3514.37.10.1915

Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. L. Berowitz (Ed.), Advances in Experimental Psychology (Vol. 19, pp. 124-203). New York, NY: Academic Press.

Pew Research Center. (2018, February 5). Social media fact sheet. Retrieved February 24, 2018 from

Porter Novelli. (2020). Porter Novelli’s 2020 executive purpose study. Retrieved from

Porter Novelli. (2021). Porter Novelli’s 2021 purpose perception study. Retrieved from

Roselius, T. (1971). Consumer rankings of risk reduction methods. The Journal of Marketing, 35 (1), 56-61.

Rosenberg, A. (2018, January 25). In three years, LGBT Americans have gone from triumph to backlash. The Washington Post, Retrieved February 20, from

Samu, S., & Wymer, W. (2009). The effect of fit and dominance in cause marketing communications. Journal of Business Research, 62(4), 432-440.

Semaan, B., Faucett, H., Robertson, S., Maruyama, M., & Douglas, S. (2015, February). Navigating imagined audiences: Motivations for participating in the online public sphere. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 1158-1169). ACM.

Slater, M. D., & Rouner, D. (1996). How message evaluation and source attributes may influence credibility assessment and belief change. Journalism & Mass Communication Quarterly, 73(4), 974-991. doi: 10.1177/107769909607300415

Tefertiller, A. C. (2018). Like us on Facebook: social capital, opinion leadership, and social media word-of-mouth for promoting cultural goods. The Journal of Social Media in Society, 7(2), 274-296.

Tetreault, M. K. T. (1986). Integrating women’s history: The case of United States history high school books. The History Teacher, 19(2), 211-262.

Turner, J. C., & Onorato, R. S. (1999). Social identity, personality, and the self-concept: A selfcategorization perspective. In T. R. Tyler, R. M. Kramer, & O. P. John (Eds.), The Psychology of The Social Self (pp. 11-46). New York, NY: Lawrence Erlbaum.

Willnat, L., Lee, W., & Detenber, B. H. (2002). Individual‐level predictors of public outspokenness: A test of the spiral of silence theory in Singapore. International Journal of Public Opinion Research, 14(4), 391-412.

Woodside, A. G., & Delozier, M. W. (1976). Effects of word of mouth advertising on consumer risk taking. Journal of Advertising, 5(4), 12-19.

Yeh, Y. H., & Choi, S. M. (2011). MINI-lovers, maxi-mouths: An investigation of antecedents to eWOM intention among brand community members. Journal of Marketing Communications, 17(3), 145-162.