2006/12/01 by José J. Ramasco, Jose J. Ramasco
Decision Sciences · Physics and Astronomy · #Complex Network Analysis Techniques #Game Theory and Applications #Opinion Dynamics and Social Influence #physics.soc-ph
paper · pdf · doi:10.1140/epjst/e2007-00069-9
published as European Physical Journal ST 143, 47 (2007) · 5 pages, 2 figures, proc. Workshop on Complex Systems, Santander Spain, To appear in EPJ B
arxiv created 2006/12/01 · openalex publication_date 2007/04/01 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
Random graphs are useful tools to study social interactions. In particular, the use of weighted random graphs allows to handle a high level of information concerning which agents interact and in which degree the interactions take place. Taking advantage of this representation, we recently defined a magnitude, the Social Inertia, that measures the eagerness of agents to keep ties with previous partners. To study this magnitude, we used collaboration networks that are specially appropriate to obtain valid statistical results due to the large size of publically available databases. In this work, I study the Social Inertia in two of these empirical networks, IMDB movie database and condmat. More specifically, I focus on how the Inertia relates to other properties of the graphs, and show that the Inertia provides information on how the weight of neighboring edges correlates. A social interpretation of this effect is also offered.