Sunbelt XXXI International Network for Social Network ... - INSNA

Representation Of Complex Cognitive Pattern StratificationEvans, Carolyn A.; Woelfel, JosephPoster SessionSAT.PM3The stratification of eight large cognitive patterns (anthropology, communication, economics, geography, library and information science, political science,psychology, and sociology) was examined using 2008 interdisciplinary citations and journals. Networks were developed for the 13‐21 journals (depending ondiscipline) that appeared as a top 5 journal in at least one of the 8 ranking methods available in the Journal Citation Report (JCR) database. Asymmetries ininformation flow between pairs of disciplines are considered indicators of gradients. “Higher” disciplines exert greater influence over “lower” disciplines.Return On Investment Of Teachers’ Social NetworksKim, Chong MinPoster SessionEducation, Decision‐making Structures, agent‐based modeling, Return on InvestmentSAT.PM3Social network could be formed randomly or strategically depending on the types and processes of social networks (Jackson, 2008). Previous social exchangetheories based on sociological perspective have explained that repeated social network could reduce uncertainty, which leads to relational commitment. Inaddition, other studies based psychological perspective have insisted that that repeated social network could produce positive emotion, which leads torelational commitment (Lawler and Yoon, 1996). And recent study integrated sociological and psychological theories into an economic model of utility in orderto maximize utility at equilibrium condition (Coleman, 1990; Frank and Maroulis, 2009). However, two key challenges still remain when we model strategicnetwork formation; to model the costs and benefits of network and to model the effect of individual incentives on network outcomes (Jackson, 2008). Thus,the purpose of this study will integrate three types of costs and benefits into the model of return on investment of social network to model the mechanism ofstrategic social network formation. Research questions will be Can the return on investment of social network model the mechanism of strategic socialnetwork formation? Computational simulation studies will be conducted by using agent‐based modeling. Anticipated results will be that the return oninvestment of social network could model the mechanism of strategic social network formation and increasing individuals’ return on investment of socialnetwork may not lead to efficient knowledge flow and collective change.