Artem Zakharchenko


Media posts spread throughout social networks due to their ability to call the readers to actions which is the sign of their influence. These actions can be considered both as social and communicative. Therefore, they can be studied in relation with other social actions taken by the same users offline: participation in mass protests, purchase of goods, downloading mobile applications, etc.

The research has shown that not every share means the readiness for such offline actions. Most often this readiness is observed if media posts on a particular topic are shared through goal-rational actions and at the same time have a high influence on the audience. This influence is assessed by the author’s methodology of determining the interactive potential.

The research has also found that while the news is spread among the politically active Ukrainians, the proportion of different types of shares varies depending on the indicator of publication influence on the audience. For publications with high influence indicator, goal-rational and value-based shares are the most typical and if the indicator is low, the affective spreading occurs.


social action, social networks, interactive potential, information spreading, media audience


Bagozzi, R. P. & Dholakia, U. M. (2006). Open sources of software user communities: A study of participation in Linux user groups. Management Science, 52 (7), 1099–1115.

Bagozzi, R. P. & Lee, K. H. (2002). Multiple routes for social influence: the role of compliance, internalization, and social identity. Social Psychology Quarterly, 65 (3), 226–247.

Cheung, C. M. K. & Lee, M. K. O. (2010). A theoretical model of intentional social action in online social networks. Decision Support Systems, 49, 24–30.

Ferrara, E. (2017). Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election. First Monday, 22 (8).

Guo, L., Tan, E., Chen, S., Zhang, X., & Zhao, Y. E. (2009). Analyzing patterns of user content generation in online social networks. In: “KDD’09”(pp.369–378).

Habermas, J. (1990) Moral Consciousness and Communicative Action. Cambridge. Massachusetts: MIT Press.

Kelman, H. C. (1958). Compliance, identification, and internalization: three processes of attitude change. Journal of Conflict Resolution, 2 (1). 51–60.

da Rocha, A. F., Massad, E., dos Santos, P. C. C., & Pereira, A. Jr. (2015). A neurobiologically inspired model of social cognition: Memes spreading in the Internet. Biologically Inspired Cognitive Architectures, 141, 86–96.

Tuomela, R. (2008). Collective intentionality and group reasons. In: H. B. Schmid, & K. Schulte-Ostermann, & N. Psarros (Eds.), Concepts of sharedness: Essays on collective intentionality (pp.3–19). Ontos Verlag.

Varol, O., Ferrara, E., Menczer, F., & Flammini, A. (2017). Early detection of promoted campaigns on social media. EPJ Data Science, 6(1),13.

Weber. М. (2000). Basic concepts in sociology. New York: Kensington Publishing.

Xiao-Liang, S., Cheung, C. M. K., & Lee, M. K. O. (2013). Perceived critical mass and collective intention in social media-supported small group communication. International Journal of Information Management, 33, 707–715.

Zakharchenko, A. (2017). Evaluating the social impact of Internet media news. Civitas et Lex, 2(14), 7-21.

Zhao, L., Lu, Y., Wang, B., Chau, P. Y. K., & Zhang, L. (2012). Cultivating the sense of belonging and motivating user participation in virtual communities: A social capital perspective. International Journal of Information Management, 32(6), 574–588.

Zakharchenko, А. (2016). Method for studying the dynamics of the Ukrainians’ interest to political “soap operas” based on measuring the interactive potential. Scientific Notes of the Institute of Journalism, 64, 34-43



  • There are currently no refbacks.

Copyright (c) 2018

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Siauliai university