D. Easley and J. Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World, 2010.
DOI : 10.1017/CBO9780511761942

D. Kempe and J. Kleinberg, Maximizing the spread of influence through a social network, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, pp.137-146, 2003.
DOI : 10.1145/956750.956769

F. Chua, H. Lauw, and E. Lim, Generative Models for Item Adoptions Using Social Correlation, IEEE Transactions on Knowledge and Data Engineering, vol.25, issue.9, pp.2036-2048, 2013.
DOI : 10.1109/TKDE.2012.137
URL : http://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article%3D2549%26context%3Dsis_research

S. Myers, C. Zhu, and J. Leskovec, Information diffusion and external influence in networks, Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '12, pp.33-41, 2012.
DOI : 10.1145/2339530.2339540
URL : http://cs.stanford.edu/people/jure/pubs/ext-kdd12.pdf

W. Chen, Y. Yuan, and L. Zhang, Scalable Influence Maximization in Social Networks under the Linear Threshold Model, 2010 IEEE International Conference on Data Mining, pp.88-97, 2010.
DOI : 10.1109/ICDM.2010.118

W. Chen, W. Lu, and N. Zhang, Time-critical influence maximization in social networks with time-delayed diffusion process, AAAI. AAAI, pp.592-598, 2012.

A. Borodin, Y. Filmus, and J. Oren, Threshold Models for Competitive Influence in Social Networks, pp.539-550, 2010.
DOI : 10.1137/080714452
URL : http://www.cs.toronto.edu/~bor/wine-final.pdf

N. Pathak, A. Banerjee, and J. Srivastava, A Generalized Linear Threshold Model for Multiple Cascades, 2010 IEEE International Conference on Data Mining, pp.965-970, 2010.
DOI : 10.1109/ICDM.2010.153

A. Goyal, W. Lu, and L. V. Lakshmanan, SIMPATH: An Efficient Algorithm for Influence Maximization under the Linear Threshold Model, 2011 IEEE 11th International Conference on Data Mining, pp.211-220, 2011.
DOI : 10.1109/ICDM.2011.132

R. Narayanam and Y. Narahari, A Shapley Value-Based Approach to Discover Influential Nodes in Social Networks, IEEE Transactions on Automation Science and Engineering, vol.8, issue.1, pp.130-147, 2011.
DOI : 10.1109/TASE.2010.2052042

S. Bharathi, D. Kempe, and M. Salek, Competitive Influence Maximization in Social Networks, pp.306-311, 2007.
DOI : 10.1007/978-3-540-77105-0_31
URL : http://www-rcf.usc.edu/~dkempe/publications/viral-competitive.pdf

S. Goyal and M. Kearns, Competitive contagion in networks, STOC. ACM, pp.759-774, 2012.
DOI : 10.2139/ssrn.1950644
URL : http://www.cis.upenn.edu/%7Emkearns/papers/GoyalKearnsSTOCFinal.pdf

S. Myers and J. Leskovec, Clash of the Contagions: Cooperation and Competition in Information Diffusion, 2012 IEEE 12th International Conference on Data Mining, pp.539-548, 2012.
DOI : 10.1109/ICDM.2012.159

A. Zarezade, A. Khodadadi, M. Farajtabar, H. Rabiee, and H. Zha, Correlated cascades: Compete or cooperate, AAAI, pp.238-244, 2017.

D. Godes, The Strategic Impact of References in Business Markets, Marketing Science, vol.31, issue.2, pp.257-276, 2012.
DOI : 10.1287/mksc.1110.0695

R. Van-der-lans, G. Van-bruggen, J. Eliashberg, and B. Wierenga, A Viral Branching Model for Predicting the Spread of Electronic Word of Mouth, Marketing Science, vol.29, issue.2, pp.348-365, 2010.
DOI : 10.1287/mksc.1090.0520

S. Aral and D. Walker, Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks, Management Science, vol.57, issue.9, pp.1623-1639, 2011.
DOI : 10.1287/mnsc.1110.1421

R. Meyer, S. Zhao, and J. Han, Biases in Valuation vs. Usage of Innovative Product Features, Marketing Science, vol.27, issue.6, pp.1083-1096, 2008.
DOI : 10.1287/mksc.1080.0367

M. Braun and A. Bonfrer, Scalable Inference of Customer Similarities from Interactions Data Using Dirichlet Processes, Marketing Science, vol.30, issue.3, pp.513-531, 2011.
DOI : 10.1287/mksc.1110.0640

P. Boer, D. P. Kroese, S. Mannor, and R. Y. Rubinstein, A Tutorial on the Cross-Entropy Method, Annals of Operations Research, vol.16, issue.3, pp.19-67, 2005.
DOI : 10.1137/S0363012901385691