Modeling of Market Segmentation in Social Networks and Media

Author(s):  
Alexandros A. Plessias ◽  
Dimitrios K. Nasiopoulos ◽  
Despina S. Giakomidou
2018 ◽  
Vol 38 (4) ◽  
pp. 387-404
Author(s):  
Ruth Meyer ◽  
Huw Vasey

Postwar migration to “western” countries has gone hand in hand with the development of ethnically segmented labor markets, particularly in low-skill roles where entry requirements are minimal. While numerous theories have been forwarded as to why such situations occur, it has remained difficult to empirically test the relative impact of the many interacting processes that produce segmentation in the labor market. In this article, we investigate the processes of ethnic segmentation in low-skilled labor markets, where referral hiring is the norm, with particular reference to the role of ethnically homogeneous social networks and forms of discrimination. We employ an agent-based modeling approach, adapting key elements from Waldinger and Lichter’s widely cited networked explanation of ethnic labor market segmentation. This approach allows us to provide a different lens on theories of ethnic labor market segmentation, investigating the relative impacts of different causal processes that are difficult to investigate in this way using other social science approaches. The overall results from our model indicate that ethnically homogeneous social networks have the effect of increasing the level of ethnic segmentation within a referral-based labor market, but that these networks also help immigrant populations grow and protect them from the negative impacts of employer discrimination. Furthermore, these networks have a greater impact on labor market segmentation than discrimination alone. In conclusion, this sociologically informed agent-based model provides important insights into the manner and extent in which changes in social conditions may affect population-level phenomena.


Author(s):  
Mark E. Dickison ◽  
Matteo Magnani ◽  
Luca Rossi

2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.


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