Homogeneity in Social Groups of Iraq

Homogeneity in Social Groups of Iraqis Jon Gresham, Farouk Saleh, Shara Majid June 2006 With appreciation to the Royal Institute for Inter-Faith Studies for initiating the Second World Congress for Middle Eastern Studies, this paper summarizes findings on homogeneity in community-level social groups derived from inter-ethnic research conducted during 2005 among Iraqi Arabs and Kurds living in the city of Basra, Iraq, and in the Netherlands. We found that perceptions towards out-groups were not based on religion, ethnicity, class, or location as in traditional individual-focused social networks. Patterns of perception towards out-groups seemed to be rooted in homogeneous social sub-groups with combinations of these factors. This research project used a 192-item survey of two hundred Iraqi business owners and managers in Iraq and in the Netherlands. It measured homogeneity of social group memberships. Survey elements included items drawn from the World Values Surveys (Inglehart), the Social Capital Community Benchmark Survey (Roper Center), and the Social Capital Inventory (Narayan and Cassidy). Homogeneity, relationship segregation, social trust, and community influence in social networks were estimated through indices reflecting components of social relationships in priority in-groups emerging from factor analysis of survey responses. Other indices included civic participation (socialization), perceptions of threat from out-groups, ethnic and religious identity, social trust, personal security, and contribution to community-based resources. Uniformity of responses to certain items about out-groups corresponded to findings by other authors on segregation and membership in social networks (Burt 1997, Buskins 2005, Inglehart 2004, Narayan and Cassidy 2001, Putnam 1995). This work was an expansion on a study on perceptions of threat from out-groups among Iraqis in five locations conducted in 2003 (Gresham 2004). This paper presents the following major sections: I. Introduction II. Purpose III. Background IV. Methodology V. Results VI. Reporting Process VII. Conclusions VIII. Further Work IX. Appendix X. End Notes *Jon Gresham, European Research Centre On Migration & Ethnic Relations, University of Utrecht, Netherlands Farouk Saleh, University of Tilburg, Netherlands Shara Majid, Erasmus University, Netherlands See other reports at: http://www.CivilSocietyIraq.seedwiki.co

Origin of peer influence in social networks

Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends' friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.Financial support by FEDER through POFC-COMPETE and by FCT-Portugal is gratefully acknowledged through Grants No. SFRH/BD/77389/2011, No. SFRH/BPD/90936/2012, No. PTDC/MAT/122897/2010, No. EXPL/EEI-SII/2556/2013, No. PEst-OE/EEI/LA0021/2013, and No. PEst-OE/BIA/UI4050/2014

Social Networks, Sectors and Occupational Attainment in Urban China

Since the late 1970s, the People’s Republic of China has experienced a progressive market transition that has led to profound changes in organizations. The development of product market has nurtured the emergence and growth of the private sector, two parallel while competing sectors, the state sector and the private sector have coexisted since then. China has been a “relationship based” society since ancient times, social networks as an efficient channel have been frequently used during job searching process. Do social networks still have effects on job attainment during the transition to a market economy? From macro structural perspective, do social networks have distinctive influence on job attainment across different sectors, namely state sector and private sector? Based on the dataset of “Job Searching and Social Networks” (JSNet 2009), which is drawn from eight big cities, Xi’an, Changchun, Jinan, Shanghai, Xiamen, Guangzhou, Tianjin, and Lanzhou. I assess the variation of social networks in different sectors by splitting the dataset into two parts (the state sector and the private sector), and organizing occupational attainment into three categories: administrative/managerial positions, professional positions and ordinary workers. The findings show that there have been continuity and significant effects of social networks in obtaining occupations in both state sector and private sector across the transition period. Taking Chinese cultural background into consideration, strong ties play a more imperative role in job attainment as compared to weak ties. Significant variations of social networks exist across different sectors: network mechanism works more effectively in the state sector than the private sector; regarding state sector, job applicants who use network methods have greater probabilities to secure administrative/managerial jobs and ordinary jobs in comparison to professional positions, while in private sector, social networks only have effects on searching for administrative/managerial occupations, reflecting the functions of both the persistence of institutions and emerging market forces

Peer Effects and Peer Avoidance: Epidemic Diffusion in Coevolving Networks

We study the long-run-emergency of behavioral patterns in dynamic complex networks. Individuals display two kinds of behavior: G("good") or B ("bad"). We assume that agents have an innate tendency towards G, but can also be led towards B though the influence of peer bad behavior. We model the implications of those peer effects as an epidemic process in the standard SIS (Susceptible-Infected-Susceptible) framework. The key novelty of our model is that, unlike in received epidemic literature, the network is taken to change over time within the same time scale as behavior. Specifically, we posit that links connecting two G agents last longer, reflecting the idea that B agents tend to be avoided. The main concern of the paper is to understand the extent to which such biased network turnover may play a significant role in supporting G behavior in a social system. And indeed we find that network coevolution has nontrivial and interesting effects on long-run behavior. This yields fresh insights on the role of (endogenous) peer pressure on the diffusion of (a)social behavior as well as on the traditional study of disease epidemics.Coevolutionary networks, diffusion of behavior, social dilemma, epidemics

Binary Dynamics On Star Networks Under External Perturbations.

We study a binary dynamical process that is a representation of the voter model with two candidates and opinion makers. The voters are represented by nodes of a network of social contacts with internal states labeled 0 or 1 and nodes that are connected can influence each other. The network is also perturbed by opinion makers, a set of external nodes whose states are frozen in 0 or 1 and that can influence all nodes of the network. The quantity of interest is the probability of finding m nodes in state 1 at time t. Here we study this process on star networks, which are simple representations of hubs found in complex systems, and compare the results with those obtained for networks that are fully connected. In both cases a transition from disordered to ordered equilibrium states is observed as the number of external nodes becomes small. For fully connected networks the probability distribution becomes uniform at the critical point. For star networks, on the other hand, we show that the equilibrium distribution splits in two peaks, reflecting the two possible states of the central node. We obtain approximate analytical solutions for the equilibrium distribution that clarify the role of the central node in the process. We show that the network topology also affects the time scale of oscillations in single realizations of the dynamics, which are much faster for the star network. Finally, extending the analysis to two stars we compare our results with simulations in simple scale-free networks.9204281

Marketing Applications of Social Tagging Networks

This dissertation focuses on marketing applications of social tagging networks. Social tagging is a new way to share and categorize content, allowing users to express their perceptions and feelings with respect to concepts such as brands and firms with their own keywords, “tags.” The associative information in social tagging networks provides marketers with a rich source of information reflecting consumers’ mental representations of a brand/firm/product. The first essay presents a methodology to create “social tag maps,” brand associative networks derived from social tags. The proposed approach reflects a significant improvement towards understanding brand associations compared to conventional techniques (e.g., brand concept maps and recent text mining techniques), and helps marketers to track real-time updates in a brand’s associative network and dynamically visualize the relative competitive position of their brand. The second essay investigates how information contained in social tags acts as proxy measures of brand assets that track and predict the financial valuation of firms using the data collected from a social bookmarking website, del.icio.us, for 61 firms across 16 industries. The results suggest that brand asset metrics based on social tags explain stock return. Specifically, an increase in social attention and connectedness to competitors is shown to be positively related to stock return for less prominent brands, while for prominent brands associative uniqueness and evaluation valence is found to be more significantly related to stock return. The findings suggest to marketing practitioners a new way to proactively improve brand assets for impacting a firm’s financial performance. The third essay investigates whether the position of products on social tagging networks can predict sales dynamics. We find that (1) books in long tail can increase sales by being strongly linked to well-known keywords with high degree centrality and (2) top sellers can be better sellers by creating dense content clusters rather than connecting them to well-known keywords with high degree centrality. Our findings suggest that marketing managers better understand a user community’s perception of products and potentially influence product sales by taking into account the positioning of their products within social tagging networks

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalised clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking.Comment: 16 pages, 5 figure

Postpartum Smoking Relapse: Qualitative Research to Understand the Role of the Social Environment

While up to 45% of women quit smoking during pregnancy, nearly 80% return to smoking within a year after delivery. Current interventions to prevent this return have had limited success. The aim of this study was to use the Theory of Planned Behavior to understand the factors influencing intention to resume smoking postpartum, specifically focusing on the role of subjective norms, or the social environment. During the postpartum hospital stay, we conducted in-depth, individual interviews with 24 women who had quit smoking during pregnancy. Over 300 pages of transcripts were analyzed by all four investigators using qualitative methods to identify common themes facilitated by Atlas.ti software. Respondents were predominately white (63%) and primipara (54%) with a mean age of 26. When reflecting on their experiences of being a smoker, the women emphasized the importance of their social relationships. Common themes were: 1) virtually all were embedded in large, complex social networks of smokers (partners, family, friends, co-workers) that influenced their smoking behavior, 2) the subjective norm (the perceived social pressure) for many women was that, while smoking during pregnancy is unacceptable, smoking after pregnancy is tolerable, and 3) partners were particularly influential on these womens smoking behaviors. In conclusion, we found that social environment played a large role in these women\u27s past smoking behavior and future intentions. Thus, this factor may continue to influence their behavior after pregnancy. Further research is needed to establish the generalizability of these findings; however, our study suggests that the influence of the social environment should be integrated into postpartum smoking interventions