2013/06/04 by Biplab Bhattacherjee, S. S. Manna, Animesh Mukherjee
Computer Science · Mathematics · Physics and Astronomy · Psychology · Social Sciences · #Algorithm #Analogy #Artificial intelligence #Bipartite graph #Cluster (spacecraft) #Complex Network Analysis Techniques #Computer science #Epistemology #Evolutionary Game Theory and Cooperation #Graph #Information retrieval #Mathematical economics #Mathematics #Mutual information #Opinion Dynamics and Social Influence #Percolation (cognitive psychology) #Phenomenon #Psychology #Scaling #Sequence (biology) #Set (abstract data type) #Sorting #Statistics #Theoretical computer science #Zipf's law #cond-mat.stat-mech #cs.SI #physics.soc-ph #sort
paper · pdf · doi:10.1103/physreve.87.062808
6 pages, 7 figures
arxiv created 2013/06/04 · openalex publication_date 2013/06/17 · arxiv updated 2015/06/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We present the results of a detailed numerical study of a model for the sharing and sorting of information in a community consisting of a large number of agents. The information gathering takes place in a sequence of mutual bipartite interactions where randomly selected pairs of agents communicate with each other to enhance their knowledge and sort out the common information. Although our model is less restricted compared to the well-established naming game, the numerical results strongly indicate that the whole set of exponents characterizing this model are different from those of the naming game and they assume nontrivial values. Finally, it appears that in analogy to the emergence of clusters in the phenomenon of percolation, one can define clusters of agents here having the same information. We have studied in detail the growth of the largest cluster in this article and performed its finite-size scaling analysis.