Abstract
Today’s leading businesses have understood the role of “social” into their everyday activity. Online social networks (OSN) and social media have melt and become an essential part of every firm’s concerns. Brand advocates are the new leading triggers for company’s success in online social networks and are responsible for the long term engagement between a firm and its customers. But what can it be said about this impressive crowd of customers that are gravitating around a certain brand advocacy or a certain community? Are they as responsive to a certain message as one might think? Are they really impressed by the advertising campaigns? Are they equally reacting to a certain comment or news? How they process the everyday grey knowledge that is circulating in OSN? In fact, how impressionable they are and which are the best ways a company can get to them?
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References
Schneider, F., Feldmann, A., Krishnamurthy, B., Willinger, W.: Understanding online social network usage from a network perspective. In: Proceedings of the ACM SIGCOMM Conference on Internet Measurement, pp. 35–48 (2009)
Heidemann, J., Klier, M., Probst, F.: Online social networks: A survey of a global phenomenon. Computer Networks 56, 3866–3878 (2012)
Synthesio: Drive Customer Experience with Social Intelligence (e-book) (2014). http://synthesio.com/corporate/en/2014/uncategorized/drive-customer-experience-social-intelligence-ebook/
Liu, S., Lin, Y.: Grey Systems – Theory and Applications. Understanding Complex Systems Series. Springer, Heidelberg (2010)
Forrest, J.: A Systemic Perspective on Cognition and Mathematics. CRC Press (2013)
Delcea, C.: Not black. Not even white. Definitively grey economic systems. Journal of Grey System 26(1), 11–25 (2014)
Delcea, C., Cotfas, L.-A., Paun, R.: Grey social networks. In: Hwang, D., Jung, J.J., Nguyen, N.-T. (eds.) ICCCI 2014. LNCS, vol. 8733, pp. 125–134. Springer, Heidelberg (2014)
Delcea, C., Cotfas, L.-A., Paun, R.: Understanding Online Social Networks’ Users – A Twitter Approach. In: Hwang, D., Jung, J.J., Nguyen, N.-T. (eds.) ICCCI 2014. LNCS, vol. 8733, pp. 145–153. Springer, Heidelberg (2014)
Cotfas, L.-A., Delcea, C., Roxin, I., Paun, R.: Twitter ontology-driven sentiment analysis. In: Barbucha, D., Nguyen, N.T., Batubara, J. (eds.) New Trends in Intelligent Information and Database Systems. SCI, vol. 598, pp. 131–140. Springer, Heidelberg (2015)
Liu, S., Scarlat, E., Delcea, C.: Grey systems in economics. Theory and applications. ASE Printing house (2014) (in Romanian)
Ke, L., Xiaoliu, S., Zhongfy, T., Wenyan, G.: Grey clustering analysis method for overseas energy project investment risk decision. Systems Engineering Procedia 3, 55–62 (2012)
Wen, K.L.: A Matlab toolbox for grey clustering and fuzzy comprehensive evaluation. Advances in Engineering Software 39, 137–145 (2008)
Lin, C.H., Wu, C.H., Huang, P.Z.: Grey clustering analysis for incipient fault diagnosis in oil-immersed transformers. Expert Systems with Applications 39, 1371–1379 (2009)
Spanos, Y.E., Lioukas, S.: An examination into the causal logic of rent generation: contrasting Porter’s competitive strategy framework and the resource-based perspective. Strategic Management Journal 22, 907–934 (2001)
Wu, J., Liu, X., Li, Y., Shu, J., Liu, K.: Node Importance Evaluation in Complex Networks Based on Grey Theory. Journal of Information & Computational Science 10(17), 5629–5635 (2013)
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Delcea, C., Bradea, I., Paun, R., Scarlat, E. (2015). How Impressionable Are You? - Grey Knowledge, Groups and Strategies in OSN. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9329. Springer, Cham. https://doi.org/10.1007/978-3-319-24069-5_16
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DOI: https://doi.org/10.1007/978-3-319-24069-5_16
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