Predicting Public Interest Issue Campaign Participation on Social Media


  • Jungyun Won
  • Linda Hon
  • Ah Ram Lee



Situational theory of publics, Social media campaign, Public interest communications, Participation benefits, Social ties


This study investigates what motivates people to participate in a social media campaign in the context of animal protection issues. Structural equation modeling (SEM) tested a proposed research model with survey data from 326 respondents. Situational awareness, participation benefits, and social ties influence were positive predictors of social media campaign participation intentions. Situational awareness also partially mediates the relationship between participation benefits and participation intentions as well as strong ties influence and participation intentions. When designing social media campaigns, public interest communicators should raise situational awareness and emphasize participation benefits. Messages shared through social networks, especially via strong ties, also may be more effective than those posted only on official websites or social networking sites (SNSs).


Aldoory, L., & Sha, B. L. (2007). Elaborations of the situational theory of publics for more effective application to public relations scholarship and practice. In E. L. Toth (Ed.), The future of excellence in public relations and communication management: Challenges for the next generation (pp. 339-355). Mahwah, NJ: Erlbaum.

Aral, S., & Walker, D. (2014). Tie strength, embeddedness, and social influence: A large-scale networked experiment. Management Science, 60(6), 1352-1370. doi:10.1287/mnsc.2014.1936

Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling. Sociological Methods & Research, 16(1), 78-117. doi:10.1177/0049124187016001004

Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303-316. doi:10.1177/0049124189017003004

Boomsma, A. (1985). Nonconvergence, improper solutions, and starting values in LISREL maximum likelihood estimation. Psychometrika, 50(2), 229-242. doi:10.1007/BF02294248

Brunsting, S. & Postmes, T. (2002). Social movement participation in the digital age: Predicting offline and online collective action. Small Group Research, 33(5), 525-554. doi:10.1177/104649602237169

Cameron, G. T., & Yang, J. (1991). Effect of support and personal distance on the definition of key publics for the issue of AIDS. The Journalism Quarterly, 68(4), 620-629. doi:10.1177/107769909106800402

Carmins, E. C., & McIver, J. P. (1981). Analyzing models with unobservable variables. Social measurement: Current issues. Beverly Hills, CA: Sage.

Carty, V. (2015). Social movements and new technology (1st ed). Boulder, CO: Westview Press.

Castells, M. (2015). Networks of outrage and hopes: Social movements in the Internet age. Hoboken, NJ: John Wiley & Sons.

Cho, E., Myers, S. A., & Leskovec, J. (2011). Friendship and mobility: User movement in location-based social networks. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1082-1090. ACM. doi:10.1145/2020408.2020579

Chu, S. C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 30(1), 47-75. doi:10.2501/IJA-30-1-047-075

Earl, J., & Kimport, K. (2011). Digitally enabled social change: Activism in the internet age. Cambridge, MA: MIT Press. doi:10.7551/mitpress/9780262015103.001.0001

Dencik, L., & Leistert, O. (2015). Critical perspectives on social media and protest: Between control and emancipation. London: Rowman & Littlefield International.

Diani, M. (2000). Social movement networks virtual and real. Information, Communication & Society, 3(3), 386-401. doi:10.1080/13691180051033333

Grabowicz, P. A., Ramasco, J. J., Moro, E., Pujol, J. M., & Eguiluz, V. M. (2012). Social features of online networks: The strength of intermediary ties in online social media. PloS one, 7(1), e29358. 1-9. doi:10.1371/journal.pone.0029358

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380. doi:10.1086/225469

Granovetter, M. S. (1983). The strength of weak ties: A network theory revisited. Sociological Theory, 1(1), 201-233. doi:10.2307/202051

Grunig, J. E. (1966). The role of information in economic decision making. Journalism Monographs, 3, 1-52.

Grunig, J. E. (1989). Publics, audiences and market segments: Models of receivers of campaign messages. In C. T. Salmon (Ed.). Information campaigns: Managing the process of social change (pp. 197-226). Newbury Park, CA: Sage.

Grunig, J. E. (1997). A situational theory of publics: Conceptual history, recent challenges and new research. In D. Moss, T. MacManus, & D. Vercic (Eds.), Public relations research: An international perspective (pp. 3-46). London: International Thompson Business.

Grunig, J. E. (2003). Constructing public relations theory and practice. In B. Dervin & S. Chaffee, & L. Foreman-Wernet (Eds.), Communication, another kind of horse race: Essays honoring Richard F. Carter (pp. 85-115). Cresskill, NJ: Hampton Press.

Hamilton, P. K. (1992). Grunig's situational theory: A replication, application, and extension. Journal of Public Relations Research, 4(3), 123-149. doi:10.1207/s1532754xjprr0403_01

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York, NY: Guilford Press.

Hon, L. (2015). Digital social advocacy in the Justice for Trayvon Campaign. Journal of Public Relations Research, 27(4), 299-321. doi:10.1080/1062726X.2015.1027771

Hon, L. (2016). Social media framing within the Million Hoodies movement for justice. Public Relations Review, 42(1), 9-19. doi:10.1016/j.pubrev.2015.11.013

Ibarra, H (1993). Personal networks of women and minorities in management: A conceptual framework. Academy of Management Review, 18, 56-87. doi:10.5465/amr.1993.3997507

Jenkins, H., Shresthova, S., Gamber-Thompson, L., Kligler-Vilenchik, N., & Zimmerman, A. (2016). By any media necessary: The new youth activism, New York, NY: NYU Press.

Kebede, W., & A.K. Butterfield (2009). Social networks among poor women in Ethiopia. International Social Work, 52(3), 357–373. doi:10.1177/0020872808102069

Kim, J. N., Grunig, J. E., & Ni, L. (2010). Reconceptualizing the communicative action of publics: Acquisition, selection, and transmission of information in problematic situations. International Journal of Strategic Communication, 4(2), 126-154. doi:10.1080/15531181003701913

Kim, J. N. (2011). Public segmentation using situational theory of problem solving: Illustrating summation method and testing segmented public profiles, Prism, 8(2), 1-12. Retrieved from

Kim, J. N., & Grunig, J. E. (2011). Problem solving and communicative action: A situational theory of problem solving. Journal of Communication, 61(1), 120-149. doi:10.1111/j.1460-2466.2010.01529.x

Kline, R. B. (2005). Principle and practice of structural equation modeling (2nd ed.). New York, NY: Guilford.

Kline, R. B. (2013). Exploratory and confirmatory factor analysis. In Y. Petscher, C. Schatschneider, & D. L. Compton, (Eds.), Applied Quantitative Analysis in the Social sciences (pp. 171-207). New York, NY: Routledge.

Knoke, D., & S. Yang (2008). Social network analysis (2nd ed.). Los Angeles, CA: Sage.

Krackhardt, D. (1992). The strength of strong tie: The importance of philos in organizations. In R. Cross, A. Parker, & L. Sasson (Eds.), Networks and organizations: Structure, form, and action (pp. 216-239). Oxford, England: Oxford University Press.

Lai, E. R. (2011). Motivation: A literature review research report. Retrieved from Pearson assessments website:

Lei, M., & Lomax, R. G. (2005). The effect of varying degrees of nonnormality in structural equation modeling. Structural Equation Modeling, 12(1), 1-27. doi:10.1207/s15328007sem1201_1

Levin, D. Z., & Cross, R. (2004). The strength of weak ties you can trust: The mediating role of trust in effective knowledge transfer. Management Science, 50(11), 1477-1490. doi:10.1287/mnsc.1030.0136

Li, Z. (2016). Psychological empowerment on social media: Who are the empowered users? Public Relations Review, 42(1), 49-59. doi:10.1016/j.pubrev.2015.09.001

Ling, K., Beenen, G., Ludford, P., Wang, X., Chang, K., Li, X., Cosley, D., Frankowski, D., Terveen, L., Rashid, A. M., Resnick, P., & Kraut, R. (2005). Using social psychology to motivate contributions to online communities. Journal of Computer-Mediated Communication, 10(4). doi:10.1111/j.1083-6101.2005.tb00273.x

MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51(1), 201-226. doi:10.1146/annurev.psych.51.1.201

McAdam, D., & Paulsen, R. (1993). Specifying the relationship between social ties and activism. American Journal of Sociology, 99(3), 640-667. doi:10.1086/230319

McCarthy, J., & Zald, M. (1977). Resource mobilization and social movements: A partial theory. American Journal of Sociology, 82(6), 1212-1241. doi:10.1086/226464

Mittal, V., Huppertz, J. W., & Khare, A. (2008). Customer complaining: The role of tie strength and information control. Journal of Retailing, 84(2), pp. 195-204. doi:10.1016/j.jretai.2008.01.006

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20-38. doi:10.2307/1252308

Nevitt, J., & Hancock, G. R. (2001). Performance of bootstrapping approaches to model test statistics and parameter standard error estimation in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 8(3), 353–377. doi:10.1207/s15328007SEM0803_2

Nunnally, J. C., & Bernstein, I. (1978). Psychometric Theory (2nd ed.). New York, NY: McGraw-Hill.

Obaa, B. B., & Mazur, R. E. (2016). Social network characteristics and resource access among formerly displaced households in Lira, Uganda. Disasters, 41(3), 468-486. doi:10.1111/disa.12210

Oberschall, A. (1973). Social conflict and social movements. Englewood Cliffs, NJ, Prentice Hall.

Paek, H. J., Hove, T., Jung, Y., & Cole, R. T. (2013). Engagement across three social media platforms: An exploratory study of a cause-related PR campaign, Public Relations Review, 39, 526-533. doi:10.1016/j.pubrev.2013.09.013

Parks, M. R., & Floyd, K. (1996). Making friends in cyberspace. Journal of Computer‐Mediated Communication, 1(4), JCMC144. doi:10.1111/j.1083-6101.1996.tb00176.x

Pigg, K. E., & Crank, L. D. (2004). Building community social capital: The potential and promise of information and communications technologies, Journal of Community Informatics, 1(1), 58-73. Retrieved from

Postmes, T., & Brunsting, S. (2002). Collective action in the age of the internet: Mass communication and online mobilization. Social Science Computer Review, 20(3), 290-301. doi:10.1177/089443930202000306

Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36, 717-731. doi:10.3758/BF03206553

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879-891. doi:10.3758/BRM.40.3.879

Reis, H. T., & Judd, C. M. (2014. Handbook of research methods in social and personality psychology (2nd ed.). New York, NY: Cambridge University Press.

Robins, R. W., Fraley, R. C., & Krueger, R. F. (2007). Handbook of research methods in personality psychology. NewYork, NY: Guilford Press.

Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67. doi:10.1006/ceps.1999.1020

Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99(6), 323-338. doi:10.3200/JOER.99.6.323-338

Schumacker, R. E., & Lomax, R. G. (2004). A beginner's guide to structural equation modeling. London: Psychology Press.

Sequeira, J., Mueller, S. L., & McGee, J. E. (2007). The influence of social ties and self-efficacy in forming entrepreneurial intentions and motivating nascent behavior. Journal of Developmental Entrepreneurship, 12(3), 275-293. doi:10.1142/S108494670700068X

Shan, Y., & King, K. W. (2015). The effects of interpersonal tie strength and subjective norms on consumers' brand-related eWOM referral intentions. Journal of Interactive Advertising, 15(1), 16-27. doi:10.1080/15252019.2015.1016636

Shirky, C. (2008). Here comes everybody: The power of organizing without organizations. New York, NY: Penguin.

Shirky, C. (2011). The political power of social media: Technology, the public sphere, and political change. Foreign Affairs, 90(1), 28-41. Retrieved from

Smith, T., Coyle, J. R., Lightfoot, E., & Scott, A. (2007). Reconsidering models of influence: The relationship between consumer social networks and word-of-mouth effectiveness. Journal of Advertising Research, 47(4), 387–397. doi:10.2501/S0021849907070407

Soper, D.S. (2016). A-priori Sample Size Calculator for Multiple Regression [Computer software]. Retrieved from:

Social media fact sheet. (2017). Retrieved from Pew Research Center website:

Wang, R. Y., & Fesenmaier, D. R. (2002). Measuring the needs of virtual community members: An empirical study of an online travel community. In Information and communication technologies in tourism 2002: Proceeding of the International Conference in Innsbruck, Austria, 2002 (pp. 105-114). Springer-Verlag Wien. Retrieved from

Wang, R.Y., & Fesenmaier, D. R. (2004). Toward understanding members’ general participation in and active contribution to an online travel community. Tourism Management, 25(6), 709-722. doi:10.1016/j.tourman.2003.09.011

Wang, Y., Yu, Q., & Fesenmaier, D. (2002). Defining the virtual tourist community: Implications for tourism marketing. Tourism Management, 23(4), 407-417. doi:10.1016/S0261-5177(01)00093-0

Wilson, D. J. (1990). Science, community, and the transformation of American philosophy, 1986–1930. Chicago, IL: University of Chicago Press.

Wirtz, J., & Chew, P. (2002). The effects of incentives, deal proneness, satisfaction and tie strength on word-of-mouth behavior. International Journal of Service Industry Management, 13(2), 141-162. doi:10.1108/09564230210425340

Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample size requirements for structural equation models an evaluation of power, bias, and solution propriety. Educational and Psychological Measurement, 76(6), 913-934. doi:10.1177/0013164413495237






Original Research