Bibliographic Details
| Title: |
Organization of networks with tagged nodes and biased links: A priori distinct communities: The case of intelligent design proponents and Darwinian evolution defenders |
| Authors: |
Rotundo, G.1 giulia.rotundo@uniroma1.it, Ausloos, M.2 marcel.ausloos@ulg.ac.be |
| Source: |
Physica A. Dec2010, Vol. 389 Issue 23, p5479-5494. 16p. |
| Subjects: |
Graph theory, Sentiment analysis, Biological evolution, Mathematical symmetry, Directed graphs, Citation networks |
| Abstract: |
Abstract: Among the topics of opinion formation it is of interest to observe the characteristics of networks with a priori distinct communities. The citation network(s) between selected members of the Neocreationist and Intelligent Design and the Darwinian Evolution communities are unfolded through the available internet citations. The resulting adjacency matrix is not symmetric. A generalization of considerations pertaining to the case of networks with tagged nodes and biased links, directed or undirected, is presented. The main characteristic coefficients describing the structure of such networks are outlined. The structural features are discussed searching for statistical aspects of the communities. The degree distributions, each network’s assortativity, specific global and local clustering coefficients and the Average Overlap Indices are especially calculated since the distribution of elements in the rectangular submatrices represent inter-community connections. The various closed and open triangles made from nodes, distinguishing the community, are listed. The -scores of patterns are calculated. One can distinguish between opinion leaders, followers and main rivals and briefly interpret their relationships through intuitively expected behavior in defence of an opinion. Suggestions for more elaborate models describing such communities and their subsequent structures are found in conclusions. [ABSTRACT FROM AUTHOR] |
|
Copyright of Physica A is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |
