Intertwined Viral Marketing through Online Social Networks

Traditional viral marketing problems aim at selecting a subset of seed users for one single product to maximize its awareness in social networks. However, in real scenarios, multiple products can be promoted in social networks at the same time. At the product level, the relationships among these products can be quite intertwined, e.g., competing, complementary and independent. In this paper, we will study the "interTwined Influence Maximization" (i.e., TIM) problem for one product that we target on in online social networks, where multiple other competing/complementary/independent products are being promoted simultaneously. The TIM problem is very challenging to solve due to (1) few existing models can handle the intertwined diffusion procedure of multiple products concurrently, and (2) optimal seed user selection for the target product may depend on other products' marketing strategies a lot. To address the TIM problem, a unified greedy framework TIER (interTwined Influence EstimatoR) is proposed in this paper. Extensive experiments conducted on four different types of real-world social networks demonstrate that TIER can outperform all the comparison methods with significant advantages in solving the TIM problem.

[1]  Matthew Richardson,et al.  Mining knowledge-sharing sites for viral marketing , 2002, KDD.

[2]  Xi Chen,et al.  The approximation complexity of win-lose games , 2007, SODA '07.

[3]  Foster Provost,et al.  Audience selection for on-line brand advertising: privacy-friendly social network targeting , 2009, KDD.

[4]  Philip S. Yu,et al.  Influence Maximization Across Partially Aligned Heterogenous Social Networks , 2015, PAKDD.

[5]  Nisheeth Shrivastava,et al.  Viral Marketing for Multiple Products , 2010, 2010 IEEE International Conference on Data Mining.

[6]  Paul W. Goldberg,et al.  The complexity of computing a Nash equilibrium , 2006, STOC '06.

[7]  Stefan M. Wild,et al.  Maximizing influence in a competitive social network: a follower's perspective , 2007, ICEC.

[8]  Andreas Krause,et al.  Cost-effective outbreak detection in networks , 2007, KDD '07.

[9]  Yun Chi,et al.  Identifying opinion leaders in the blogosphere , 2007, CIKM '07.

[10]  Philip S. Yu,et al.  Community Detection for Emerging Networks , 2015, SDM.

[11]  Éva Tardos,et al.  Maximizing the Spread of Influence through a Social Network , 2015, Theory Comput..

[12]  Shishir Bharathi,et al.  Competitive Influence Maximization in Social Networks , 2007, WINE.

[13]  Jimeng Sun,et al.  A Survey of Models and Algorithms for Social Influence Analysis , 2011, Social Network Data Analytics.

[14]  Wei Chen,et al.  Scalable influence maximization for prevalent viral marketing in large-scale social networks , 2010, KDD.

[15]  Evangelos Markakis,et al.  A Game-Theoretic Analysis of a Competitive Diffusion Process over Social Networks , 2012, WINE.

[16]  Xi Chen,et al.  Computing Nash Equilibria: Approximation and Smoothed Complexity , 2006, 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06).

[17]  Pradeep Dubey,et al.  Competing for Customers in a Social Network: The Quasi-linear Case , 2006, WINE.

[18]  Vahab S. Mirrokni,et al.  Optimal marketing strategies over social networks , 2008, WWW.

[19]  Wei Chen,et al.  Efficient influence maximization in social networks , 2009, KDD.

[20]  Jaideep Srivastava,et al.  A Generalized Linear Threshold Model for Multiple Cascades , 2010, 2010 IEEE International Conference on Data Mining.

[21]  Laks V. S. Lakshmanan,et al.  Discovering leaders from community actions , 2008, CIKM '08.

[22]  Wei Chen,et al.  Influence Blocking Maximization in Social Networks under the Competitive Linear Threshold Model , 2011, SDM.

[23]  Matthew Richardson,et al.  Mining the network value of customers , 2001, KDD '01.

[24]  Tim Roughgarden,et al.  Algorithmic Game Theory , 2007 .

[25]  Yifei Yuan,et al.  Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate , 2011, SDM.

[26]  Ramasuri Narayanam,et al.  Viral Marketing for Product Cross-Sell through Social Networks , 2012, ECML/PKDD.

[27]  Adam Tauman Kalai,et al.  The myth of the folk theorem , 2008, Games Econ. Behav..

[28]  Philip S. Yu,et al.  Identifying the influential bloggers in a community , 2008, WSDM '08.

[29]  Allan Borodin,et al.  Threshold Models for Competitive Influence in Social Networks , 2010, WINE.

[30]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.