The Influence of Virtual Social Networks in the Diffusion of Information and Knowledge: SME Study

Marisa Analia Sanchez, Maria Alicia Schmidt, Juana Ines Zuntini, Lucrecia Obiol


The aim of the work is to analyze the influence of virtual social networks in the dissemination of information and knowledge. The methodology is based on case study research and includes a literature review, the use of questionnaires and social network analysis. The case studies revealed a limited use of social networks, namely LinkedIn is used in institutional form to a little extent and does not contribute to the dissemination of institutional information. In the case of those who use LinkedIn as a tool for work links, they do not evidenced that the network is an important channel of transfer and absorption of information, and it does not reflect conviction regarding the contribution of social networks in the future success of the organization.


Virtual Social Networks; Information Diffusion; Knowledge Diffusion; LinkedIn; Facebook.


Agrawal, D., Budak, C., & El Abbadi, A. (2011). Information diffusion in social networks: Observing and affecting what society cares about. En Intl. Conf. on Information and Knowledge Management.

Ahlemann, F., El Arbi, F., Kaiser, M., & Heck, A. (2013). A process framework for theoretically grounded prescriptive research in the project management field. International Journal of Project Management, 31, 43-56.

Aragõn, P., Kappler, K. E., Kaltenbrunner, A., Laniado, D., & Volkovich, Y. (2013). Communication dynamics in twitter during political campaigns: The case of the 2011 spanish national election. Policy and Internet, 5(2), 183-206.

Archambault, A., & Grudin, J. (2012). A Longitudinal Study of Facebook, Linkedin, and Twitter Use. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (págs. 2741-2750). Austin: ACM.

Argote, l., & Ingram, P. (2000). Knowledge Transfer: A Basis for Competitive Advantage in Firms. Organizational behavior and Human Decision Processes, 82(1), 150-169.

Chelmis, C., & Prasanna, V. K. (2013). The role of organization hierarchy in technology adoption at the workplace. Proc. of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, 8-15.

Chelmis, C., Srivastava, A., & Prasanna, V. K. (2014). Computational models of technology adoption at the workplace. Social Network Analysis and Mining, 4(1), 1-18.

Chuang, S. (2004). A resource-based perspective on knowledge management capability and competitive advantage: an empirical investigation. Expert Systems with Applications, 27, 459-465.

Conti, M., Das, S., Bisdikian, M., Kumar, M., Ni, L., Passarella, A., . . . Zambonelli, F. (2012). Looking ahead in pervasive computing: Challenges and opportunities in the era of cyberphysical convergence. Pervasive and Mobile Computing, 8(1), 2-21.

Crowne, K. A., Goeke, R. J., & Shoemaker, M. (2015). Enhancing international assignees’ performance with online social networks. Journal of Global Mobility, 3(4), 397-417.

Darr, E., & Kurtzberg, T. (2000). An Investigation of Partner Similarity Dimensions on Knowledge Transfer. Organizational Behavior and Human Decision Processes, 82(1), 28-44.

Edwards, G. (2010). Mixed-Method Approaches to Social Network Analysis. ESRC National Centre for Research Methods.

Ellison, N., Gibbs, J., & Weber, M. (2015). The use of enterprise social networks sites for lnowledge sharing in distributed organization: the roles of organizational affordances. American behavioral Scientist, 29(1), 103-123.

Estevez, E., & Janowski, T. (2013). Electronic Governance for Sustainable Development -Conceptual Framework and State of Research. Government Information Quarterly, 30(1), S94-S109.

Etzkowitz, H. (2003). Innovation in Innovation: The Triple Helix of University-Industry-Government Relations. Social Science Information, 42(3), 293-337.

Etzkowitz, H., & Leydesddorff, L. (1995). The Triple Helix -University-Industry-Government Relations: A Laboratory for Knowledge Based Economics Development. EASST Review, 14(1), 11-19.

Fritsch, M., & Kauffeld-Monz, M. (2010). The impact of network structure on oknowledge transfer: an application of social network analysis in the context of regionanl innovation networks. The Annals of Regional Science, 44, 21-38.

Fu, X., Passarella, A., Quercia, D., Sala, A., & Strufe, T. (2016). Online Social Networks. Computer Communications, 73(Part B), 163-166.

Fuerlinger, G., Fandl, U., & Funke, T. (2015). The role of the state in the entrepreneurship ecosystem. Insights from Germany. Triple Helix, 2(3), 1-26.

Garg, R., Smith, M. D., & Telang, R. (2011). Measuring information diffusion in an online community. Journal of Management Information Systems, 28(2), 11-37.

Gilsing, V., & Duysters, G. (2008). Understanding novelty creation in exploration networks -Structural and relational embeddedness jointly considered. technovation, 28, 693-708.

Granovetter, M. (1973). The strength if weak ties. American Journal of Sociology, 78, 1360-1389.

Grant, R. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 32(4), 109-122.

Hanneman, R., & Riddle, M. (2005). Introduction to social network methods. Riverside: University of California.

Haythornthwaite, C. (1996). Social Network analysis: An Approach and Technique for the Study of Information Exchange. Library & Information Science Research, 18(4), 323-342.

He, W., & Wang, F. (2016). A process-based framework of using social media to support innovation process. Information Technology Management, 17(123).

Heimbach, I., & Hinz, O. (2016). The impact of content sentiment and emotionality on content virality. International Journal of Research in Marketing, 33(3), 695-701.

Jiang, B., Wang, L., Yang, C., Peng, S., & Li, R. (2014). Modeling the information propagation in an email communication network using an agent-based approach. Proc. GECCO 2014, 1007-1014.

Korzynski, P. (2015). Online networking and employee engagement: What current leaders do? Journal of Management Psychology, 30, 582-596.

Levy, M., Hadar, I., Te'eni, D., Unkelos-Shpigel, N., Sherman, S., & Harel, N. (2016). Social networking in an academic conference context: Insights from a case study. Information Technology and People, 29(1), 51-68.

Li, D., Zhang, Y., Xu, Z., Chu, D., & Li, S. (2016). Exploiting information diffusion feature for link prediction in sina weibo. Scientific Reports, 6.

Liang, Q., Liao, X., & Liu, J. (2017). A social ties-based approach for group decision-making problems with incomplete additive preference relations. Knowledge-Based Systems, 119, 68-86.

Lim, S. -., Kim, S. -., Park, S., & Yoon, S. -. (2011). Determining diffusion power users in a blogosphere. Information, 14(8), 2635-2653.

Lin, C., Xie, R., Guan, X., Li, L., & Li, T. (2014). Personalized news recommendation via implicit social experts. Information Sciences, 254, 1-18.

Lin, C., Xie, R., Li, L., Huang, Z., & Li, T. (2012). PRemiSE: Personalized news recommendation via implicit social experts. ACM International Conference Proceeding Series, 1607-1611.

Lipizzi, C., Iandoli, L., & Marquez, J. E. R. (2016). Combining structure, content and meaning in online social networks: The analysis of public's early reaction in social media to newly launched movies. Technological Forecasting and Social Change, 109, 35-49.

Luo, S., Du, Y., Liu, P., Xuan, Z., & Wang, Y. (2015). A study on coevolutionary dynamics of knowledge diffusion and social network structure. Expert Systems with Applications, 42, 3619-3633.

Manetti, G., & Bellucci, M. (2016). The use of social media for engaging stakeholders in sustainability reporting. Accounting, Auditing & Accountability Journal, 29(6), 985-1011.

Mozafari, N., & Hamzeh, A. (2015). An enriched social behavioural information diffusion model in social networks. Journal of Information Science, 41(3), 273-283.

Naciones Unidas. (2009). Clasificación Industrial Internacional Uniforme de todas las actividades económicas (CIIU). Revisión 4. Dpto. Asuntos Económicos y Sociales. Nueva York: Naciones Unidas.

Narayanan, M., Asur, S., Nair, A., Rao, S., Kaushik, A., Mehta, D., . . . Lalwani, R. (2012). Social Media and Business. Vikalpa: The journal for Decision Makers, 37(4), 69-111.

Palacios-Marqués, D., Popa, S., & Alguacil Mari, M. (2016). The effect of online social networks and competency-based management on innovation capability. Journal of Knowledge Management, 20(3), 499-511.

Sankar, M. V., & Ravindran, B. (2015). Parallelization of game theoretic centrality algorithms. Sadhana - Academy Proceedings in Engineering Sciences, 40(6), 1821-1843.

Shin, S., Lee, K., & Hall, D. (2014). Exploring Facebook Users´ Continuous Visiting Behaviors: Conceptual Incorporation of Facebook User Perceptions toward Companies´Facebook Fan Page Usage. Twentieth Americas Conference on Information Systems. Savannah.

Skeels, M., & Grudin, J. (2009). When social networks cross boundaries: a case study of workplace use of Facebook and Linkedin. Proc. of the ACM 2009 Intl Conf. on Supporting Group Work (p. 95-104). Florida: ACM.

Smith, A. D. (2013). Online social networking and office environmental factors that affect worker productivity. International Journal of Procurement Management, 6(5), 578-608.

Subires Mancera, M., & Olmedo Salar, S. (2013). Universidad, sociedad y networking: perspectivas ante el uso de las redes sociales de perfil académico profesional. Estudios sobre el Mensaje Periodístico, 19, 1037-1047.

Roy, S. D., & Zeng, W. (2015). Social multimedia signals: A signal processing approach to social network phenomena. Cham: Springer International Publishing.

Tang, X., Miao, Q., Quan, Y., Tang, J., & Deng, K. (2015). Predicting individual retweet behavior by user similarity: A multi-task learning approach. Knowledge-Based Systems, 89, 681-688.

Van Alstyne, M., & Brynjolfsson, E. (2005). Global village or CyberBalkans: Modeling and measuring the integration of electronic communities. Management Science, 51(6), 851-868.

Wadhwa, P., & Bhatia, M. P. S. (2015). Measuring radicalization in online social networks using markov chains. Journal of Applied Security Research, 10(1), 23-47.

Wang, Q., Lin, Z., Jin, Y., Cheng, S., & Yang, T. (2015). ESIS: Emotion-based spreader-ignorant-stifler model for information diffusion. Knowledge-Based Systems, 81, 46-55.

Wu, D., Li, C., & Lau, R. Y. K. (2015). Topic based information diffusion prediction model with external trends. 12th IEEE International Conference on E-Business Engineering, ICEBE 2015, 29-36.

Yang, C., Jiang, B., & Wang, L. (2016). Mining and modeling the information propagation in an email communication network. Proc. HCC 2016, Colombo, Sri Lanka.

Yin, R. (1994). Case Study Research: Design and Methods. Thousand Oaks: Sage Publications.

Zaglia, M., Waiguny, M., Abfalter, D., & Müller, J. (2015). The influence of online social networks on performance of small and medium enterprises: An empirical investigation of the online business to business network XING. Int. J. Entrepreneurial Venturing, 7(1), 1-23.

Full Text: PDF/ESPANHOL (Português (Brasil))


  • There are currently no refbacks.

Iberoamerican Journal of Strategic Management  e-ISSN: 2176-0756

Licença Creative Commons
Este obra está licenciado com uma Licença
Creative Commons Atribuição-NãoComercial-CompartilhaIgual 4.0 Internacional