The temporal aspects of the evidence-based influence maximization on social networksFootnote^†

^†This research was conducted in part at the Department of Computer Science and Information Systems, University of Jyvaskyla, P.O. Box 35, Jyvaskyla, FI-40014, Finland.

References

• S. Aral and D. Walker, Creating social contagion through viral product design: A randomized trial of peer influence in networks, Manag. Sci. 57 (2011), pp. 1623–1639. doi: 10.1287/mnsc.1110.1421
   Web of Science ®Google Scholar
• W.B. Arthur, Competing technologies, increasing returns, and lock-in by historical events, Econ. J. 99 (1989), pp. 116–131. doi: 10.2307/2234208
   Web of Science ®Google Scholar
• D. Arthur, R. Motwani, A. Sharma, and Y. Xu, Pricing strategies for viral marketing on social networks, in Internet and Network Economics, S. Leonardi, ed., Springer, Berlin, 2009, pp. 101–112.
   Google Scholar
• A. Campbell, Tell your friends! Word of mouth and percolation in social networks, Job-Market Paper, 2009.
   Google Scholar
• A. Campbell, Word-of-mouth communication and percolation in social networks, Amer. Econ. Rev. 103(6) (2013), pp. 2466–2498. doi: 10.1257/aer.103.6.2466
   Web of Science ®Google Scholar
• W. Chen, C. Wang, and Y. Wang, Scalable Influence Maximization for Prevalent Viral Marketing in Large-scale Social Networks, in Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, 2010, pp. 1029–1038.
   Google Scholar
• W. Chen, A. Collins, R. Cummings, T. Ke, Z. Liu, D. Rincon, X. Sun, Y. Wang, W. Wei, and Y. Yuan, Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate, in Proceedings of SIAM International Conference on Data Mining, Philadelphia, PA, 2011, pp. 379–390.
   Google Scholar
• W. Chen, W. Lu, and N. Zhang, Time-critical Influence Maximization in Social Networks with Time-delayed Diffusion Process, in Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI'11), Palo Alto, CA, 2012, pp. 592–598.
   Google Scholar
• J.A. Chevalier and D. Mayzlin, The effect of word of mouth on sales: Online book reviews, J. Market. Res. 43 (2006), pp. 345–354. doi: 10.1509/jmkr.43.3.345
   Web of Science ®Google Scholar
• F. Chierichetti, J. Kleinberg, and A. Panconesi, How to schedule a cascade in an arbitrary graph, SIAM J. Comput. 43 (2014), pp. 1906–1920. doi: 10.1137/130936580
   Web of Science ®Google Scholar
• W. De Nooy, A. Mrvar, and V. Batagelj, Exploratory Social Network Analysis with Pajek, Vol. 27, Cambridge University Press, Cambridge, 2011.
   Google Scholar
• T.N. Dinh, H. Zhang, D.T. Nguyen, and M.T. Thai, Cost-effective viral marketing for time-critical campaigns in large-scale social networks, IEEE/ACM Trans. Netw. 22(6) (2014), pp. 2001–2011.
   Google Scholar
• P. Domingos and M. Richardson, Mining the Network Value of Customers, in Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, 2001, pp. 57–66.
   Google Scholar
• E. Even-Dar and A. Shapira, A note on maximizing the spread of influence in social networks, in Internet and Network Economics, X. Deng and F.C. Graham, eds., Springer, Berlin, 2007, pp. 281–286.
   Google Scholar
• A. Goyal, F. Bonchi, L.V.S. Lakshmanan, and S. Venkatasubramanian, On minimizing budget and time in influence propagation over social networks, Soc. Netw. Anal. Min. 3 (2013), pp. 179–192. doi: 10.1007/s13278-012-0062-z
   Google Scholar
• H. Habiba, Y. Yu, T.Y. Berger-Wolf, and J. Saia, Finding spread blockers in dynamic networks, in Advances in Social Network Mining and Analysis, L. Giles, ed., Springer, Berlin, 2010, pp. 55–76.
   Google Scholar
• W.D. Hoyer and S.P. Brown, Effects of brand awareness on choice for a common, repeat-purchase product, J. Consum. Res. 17(2) (1990), pp. 141–148. doi: 10.1086/208544
   Web of Science ®Google Scholar
• R. Huang and E. Sarigöllü, How brand awareness relates to market outcome, brand equity, and the marketing mix, J. Bus. Res. 65 (2012), pp. 92–99. doi: 10.1016/j.jbusres.2011.02.003
   Web of Science ®Google Scholar
• E.T. Jaynes, Probability Theory: The Logic of Science, Cambridge University Press, Cambridge, 2003.
   Google Scholar
• D. Kempe, J. Kleinberg, and É. Tardos, Maximizing the Spread of Influence Through a Social Network, in Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, 2003, pp. 137–146.
   Google Scholar
• M. Kimura, K. Saito, and H. Motoda, Blocking links to minimize contamination spread in a social network, ACM Trans. Knowl. Discov. Data 3 (2009), pp. 1–22. doi: 10.1145/1514888.1514892
   Web of Science ®Google Scholar
• R. Kozinets, A.C. Wojnicki, S.J. Wilner, and K. De Valck, Networked narratives: Understanding word-of-mouth marketing in online communities, J. Market. 74(2) (2010), pp. 71–89. doi: 10.1509/jmkg.74.2.71
   Web of Science ®Google Scholar
• H. Li, S.S. Bhowmick, and A. Sun, Cinema: Conformity-aware Greedy Algorithm for Influence Maximization in Online Social Networks, in Proceedings of the 16th International Conference on Extending Database Technology, New York, NY, 2013, pp. 323–334.
   Google Scholar
• B. Libai, R. Bolton, M.S. Bügel, K. De Ruyter, O. Götz, H. Risselada, and A.T. Stephen, Customer-to-customer interactions: Broadening the scope of word of mouth research, J. Serv. Res. 13 (2010), pp. 267–282. doi: 10.1177/1094670510375600
   Web of Science ®Google Scholar
• B. Liu, G. Cong, D. Xu, and Y. Zeng, Time Constrained Influence Maximization in Social Networks, in ICDM, 2012, pp. 439–448.
   Google Scholar
• W. Luo and W.P. Tay, Identifying Multiple Infection Sources in a Network, in 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), Piscataway, NJ, 2012, pp. 1483–1489.
   Google Scholar
• R.K. Merton, Selected problems of field work in the planned community, Amer. Sociol. Rev. 12(3) (1947), pp. 304–312. doi: 10.2307/2086520
   Web of Science ®Google Scholar
• P.A. Naik, A. Prasad, and S.P. Sethi, Building brand awareness in dynamic oligopoly markets, Manag. Sci. 54 (2008), pp. 129–138. doi: 10.1287/mnsc.1070.0755
   Web of Science ®Google Scholar
• G.L. Nemhauser, L.A. Wolsey, and M.L. Fisher, An analysis of approximations for maximizing submodular set functions–I, Math. Program. 14 (1978), pp. 265–294. doi: 10.1007/BF01588971
   Web of Science ®Google Scholar
• M. Samadi, A. Nikolaev, and R. Nagi, A subjective evidence model for influence maximization in social networks, Omega 59 (2016), pp. 263–278. doi: 10.1016/j.omega.2015.06.014
   Web of Science ®Google Scholar
• M.G. Sangachin, M. Samadi, and L.A. Cavuoto, Modeling the spread of an obesity intervention through a social network, J. Healthcare Eng. 5 (2014), pp. 293–312. doi: 10.1260/2040-2295.5.3.293
   PubMed Web of Science ®Google Scholar
• M. Trusov, R.E. Bucklin, and K. Pauwels, Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site, J. Market. 73 (2009), pp. 90–102. doi: 10.1509/jmkg.73.5.90
   Web of Science ®Google Scholar
• Y. Wang, G. Cong, G. Song, and K. Xie, Community-based Greedy Algorithm for Mining Top-k Influential Nodes in Mobile Social Networks, in Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, 2010, pp. 1039–1048.
   Google Scholar
• S. Wasserman, Vol. 8, Cambridge university press 1994.
   Google Scholar
• W.H. Whyte Jr, The web of word of mouth, Fortune 50 (1954), pp. 140–143.
   Google Scholar
• W.W. Zachary, An information flow model for conflict and fission in small groups, J. Anthropol. Res. 33(4) (1977), pp. 452–473. doi: 10.1086/jar.33.4.3629752
   Web of Science ®Google Scholar