Shenglong Wang^1,*, Jing Yang^1,*, Xiaoyu Ding², Jianpei Zhang¹, Meng Zhao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 215-249, 2022, DOI:10.32604/cmes.2022.018050

Abstract In recent years, local community detection algorithms have developed rapidly because of their nearly linear computing time and the convenience of obtaining the local information of real-world networks. However, there are still some issues that need to be further studied. First, there is no local community detection algorithm dedicated to detecting a seed-oriented local community, that is, the local community with the seed as the core. The second and third issues are that the quality of local communities detected by the previous local community detection algorithms are largely dependent on the position of the seed and predefined parameters, respectively. To… More >

Fabián Riquelme^1,*, Rodrigo Olivares¹, Francisco Muñoz¹, Xavier Molinero³, Maria Serna²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6305-6321, 2022, DOI:10.32604/cmc.2022.021804

Abstract An influence game is a simple game represented over an influence graph (i.e., a labeled, weighted graph) on which the influence spread phenomenon is exerted. Influence games allow applying different properties and parameters coming from cooperative game theory to the contexts of social network analysis, decision-systems, voting systems, and collective behavior. The exact calculation of several of these properties and parameters is computationally hard, even for a small number of players. Two examples of these parameters are the length and the width of a game. The length of a game is the size of its smaller winning coalition, while the… More >