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Irregular cellular automata based diffusion model for influence maximization

Daliri Khomami, M. M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/CFIS.2017.8003660
  3. Abstract:
  4. Due to great communication among users in social networks, a lot of attention is paid to the spreading of information. This issue is of a huge consideration in modern viral marketing either. So far, different models have been proposed in many of which active and inactive users are cooperating in the simple form. Since the influence of individuals in spreading of information happens differently in the real world, in this article we propose a multi-state model for information spread based on cellular automata. We used different states for the proposed model as well as various levels of influence from the beginning up to the end. As an evaluation, proposed model not only has been examined with standard data corresponding to different social networks, but also has been compared with different thresholds. The results of simulations show the superiority of proposed model in comparison with linear threshold model. © 2017 IEEE
  5. Keywords:
  6. Cellular automata ; Social networks ; Fuzzy systems ; Intelligent systems ; Social networking (online) ; Diffusion model ; Influence maximizations ; Information diffusion ; linear threashold ; Linear threshold models ; Multi-state model ; Real-world ; Viral marketing
  7. Source: 5th Iranian Joint Congress on Fuzzy and Intelligent Systems - 16th Conference on Fuzzy Systems and 14th Conference on Intelligent Systems, CFIS 2017, 7 March 2017 through 9 March 2017 ; 2017 , Pages 69-74 ; 9781509040087 (ISBN)
  8. URL: https://ieeexplore.ieee.org/document/8003660