Open Access
Issue
MATEC Web Conf.
Volume 214, 2018
2018 2nd International Conference on Information Processing and Control Engineering (ICIPCE 2018)
Article Number 02001
Number of page(s) 4
Section Computer Theory and Application
DOI https://doi.org/10.1051/matecconf/201821402001
Published online 15 October 2018
  1. W. Chen, C. Wang, Y. Wang. Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining. Scalable influence maximization for prevalent viral marketing in large-scale social networks. p. 1029–1038 (2010). [Google Scholar]
  2. S. Doyle. Journal of Database Marketing & Customer Strategy Management. The role of social networks in marketing. 1, p. 60–64 (2007). [Google Scholar]
  3. M. Stelzner. Social media examiner. 2014 Social Media Marketing Industry Report. p. 1–52 (2014). [Google Scholar]
  4. D. Chaffey. Smart Insights: Social Media Marketing. Global social media research summary 2016 (2016). [Google Scholar]
  5. F. Eggers et al. Journal of small business management. Technologies that support marketing and market development in SMEs—evidence from social networks. 2, p. 270–302 (2017). [Google Scholar]
  6. E. Turban et al. Springer. Electronic Commerce 2018: A Managerial and Social Networks Perspective (2017). [Google Scholar]
  7. E. Hunter, P. Pernik International Centre for Defence and Security. The challenges of hybrid warfare (2015). [Google Scholar]
  8. J. Klausen Studies in Conflict & Terrorism. Tweeting the Jihad: Social media networks of Western foreign fighters in Syria and Iraq. 1, p. 1–22 (2015). [Google Scholar]
  9. Y. R. Kamalipour, M. Friedrichsen. Introduction: Transformation in Journalism and News Media. Digital Transformation in a Global World. p. 1–4 (2017). [Google Scholar]
  10. L. de-Marcos et al. Computers & Education. An empirical study comparing gamification and social networking on e-learning. 75, p. 82–91 (2014). [Google Scholar]
  11. L. de-Marcos et al. Computers in Human Behavior. Social network analysis of a gamified e-learning course: Small-world phenomenon and network metrics as predictors of academic performance. 60, p. 312–321 (2016). [Google Scholar]
  12. P. De Meo et al. Information Sciences. Combining trust and skills evaluation to form e-Learning classes in online social networks. 405, p. 107–122 (2017). [Google Scholar]
  13. C. Bremer, D. Univ. Bibliothek Frankfurt am Main. Weiß How to analyze participation in a (C) MOOC?p. 992–1002 (2013). [Google Scholar]
  14. M. Khalil, H. Brunner, M. Ebner. International Journal of Emerging Technologies in Learning (iJET). Evaluation grid for xMOOCs. 4, p. 40–45 (2015). [Google Scholar]
  15. J. F. Colas, P. B. Sloep, M. Garreta-Domingo. The International Review of Research in Open and Distributed Learning. The effect of multilingual facilitation on active participation in MOOCs. 4 (2016). [Google Scholar]
  16. R. I. M. Dunbar. Behavioral and brain sciences. Coevolution of neocortical size, group size and language in humans. 4, p. 681–694 (1993). [Google Scholar]
  17. R. Dunbar. Harvard University Press. Grooming, gossip, and the evolution of language (1998). [Google Scholar]
  18. R. I. M. Dunbar. Annals of human biology. The social brain hypothesis and its implications for social evolution. 5, p. 562–572 (2009). [Google Scholar]
  19. S. Shultz, R. I. M. Dunbar. I Know What You Are Thinking: Brain Imaging and Mental Privacy. The social brain hypothesis: an evolutionary perspective on the neurobiology of social behaviour. p. 13–28 (2012). [Google Scholar]
  20. W. He. Networked Public. Social Media: Tools and Space for Networked Public Communication. p. 123–167. (Springer, Berlin, Heidelberg, 2017). [Google Scholar]
  21. S. Banerjee. Interdisciplinary Description of Complex Systems: INDECS. A biologically inspired model of distributed online communication supporting efficient search and diffusion of innovation. 1, p. 10–22 (2016). [Google Scholar]

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