Open AccessThe Use of Network Metrics in Building Intelligence Early Warning Systems. The Structural Conduciveness Index
Author(s) -
Cristina Posastiuc
Publication year - 2013
Publication title -
international review of social research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.107
H-Index - 3
eISSN - 2069-8534
pISSN - 2069-8267
DOI - 10.1515/irsr-2013-0022
Subject(s) - homophily , cluster analysis , cohesion (chemistry) , group cohesiveness , reciprocity (cultural anthropology) , collective action , structural approach , sociology , political science , psychology , computer science , artificial intelligence , social psychology , economics , social science , law , structural change , chemistry , organic chemistry , politics , macroeconomics
Specific collective behavior forms (for example, mass protests) emerge only if certain conditions are met simultaneously: good structural conduciveness of the group, a pre-existing structural strain, a formed generalized belief, the appearance of precipitating factors, a grass-roots or top-down mobilization for the action and the already-formed perception that the social control instruments are no longer in the authorities’ hands. Mass protests seem to follow this ‘perfect-storm’ recipe, from Tunis’ violent protests that kick-started the ‘Arab Spring’ to the late 2011 riots in London. This paper presents and discusses how structural conduciveness could be measured using network metrics such as k-cores, clustering, cliqueness, reciprocity, cohesion, homophily, structural holes, triad closure.