Modeling Competitive Marketing Strategies in Social Networks

被引:10
作者
Goel, Rahul [1 ]
Singh, Anurag [2 ]
Ghanbarnejad, Fakhteh [3 ]
机构
[1] Natl Inst Technol Delhi, Dept Comp Sci & Engn, Delhi 110040, India
[2] Natl Inst Technol, Dept Comp Sci & Engn, Delhi, India
[3] Tech Univ Berlin, Inst Theoret Phys, Hardenbergstr 36,Sekr EW 7-1, D-10623 Berlin, Germany
关键词
Information diffusion; Social networks; Independent cascade model; Rank degree method; Game theory; Centrality; WORD-OF-MOUTH; STRENGTH; CASCADES; NODES; RUMOR;
D O I
10.1016/j.physa.2018.11.035
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
A model is developed in which two players compete to spread information in the large network. Players choose their initial seed nodes simultaneously and the information is diffused according to Independent Cascade model (ICM). The main aim of the player is to choose the seed nodes such that they will spread its information to as many nodes as possible in a social network. Here we show and discuss how the rate of spreading of information as well as seed choosing depending on topological features play roles in information diffusion process. Any node in a social network will get influenced by none or one or more than one information. We also analyzed how much fraction of nodes in different compartment changes by changing the rate of spreading of information. Finally, a game theory model is developed to obtain the Nash equilibrium based on best response function of the players. This model is based on Hotelling's model of electoral competition. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:50 / 70
页数:21
相关论文
共 50 条
[31]   Identification of multi-spreader users in social networks for viral marketing [J].
Sheikhahmadi, Amir ;
Nematbakhsh, Mohammad Ali .
JOURNAL OF INFORMATION SCIENCE, 2017, 43 (03) :412-423
[32]   Preserving Privacy Enables "Coexistence Equilibrium" of Competitive Diffusion in Social Networks [J].
Zhao, Jun ;
Zhang, Junshan .
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 2017, 3 (02) :282-297
[33]   Spread-It: A Strategic Game of Competitive Diffusion Through Social Networks [J].
Ben-Ishay, Shimon ;
Sela, Alon ;
Ben-Gal, Bad E. .
IEEE TRANSACTIONS ON GAMES, 2019, 11 (02) :129-141
[34]   SOCIAL NETWORKS AS MARKETING TOOLS FOR THE RELIGIOUS SEGMENT [J].
Stockler Pinto Bastos, Ana Clara .
REVISTA DE CIENCIAS HUMANAS DA UNIVERSIDADE DE TAUBATE, 2010, 3 (02)
[35]   Online Social Networks and Insights into Marketing Communications [J].
Acar, Adam ;
Polonsky, Maxim .
JOURNAL OF INTERNET COMMERCE, 2007, 6 (04) :55-72
[36]   Modeling and analysis of target influence in social networks [J].
Deng, Jinsheng ;
Li, Pei ;
Qiao, Fengcai ;
Zhao, Tao .
INTERNATIONAL JOURNAL OF MODERN PHYSICS B, 2022, 36 (04)
[37]   Modeling Information Dissemination in Generalized Social Networks [J].
Chou, Yu-Feng ;
Huang, Hsin-Heng ;
Cheng, Ray-Guang .
IEEE COMMUNICATIONS LETTERS, 2013, 17 (07) :1356-1359
[38]   On the, Windfall and price of friendship: Inoculation strategies on social networks [J].
Meier, Dominic ;
Pignolet, Yvonne Anne ;
Schmid, Stefan ;
Wattenhofer, Roger .
COMPUTER NETWORKS, 2014, 62 :221-236
[39]   Optimal Product-Sampling Strategies in Social Networks: How Many and Whom to Target? [J].
Schlereth, Christian ;
Barrot, Christian ;
Skiera, Bernd ;
Takac, Carsten .
INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE, 2013, 18 (01) :45-72
[40]   A note on competitive diffusion through social networks [J].
Alon, Noga ;
Feldman, Michal ;
Procaccia, Ariel D. ;
Tennenholtz, Moshe .
INFORMATION PROCESSING LETTERS, 2010, 110 (06) :221-225