Social network engineering and race in a police academy: A longitudinal analysis

This research examined an attempt to facilitate racial integration by populating squads (i.e., workgroups) in a police academy with mixes of recruits that reflected the racial demographics of the larger cohort. This was part of the social infrastructure of the academy. Additionally, a fixed seating arrangement was considered as a second element of academy infrastructure capable of impacting racial integration. We examined the consequences of these academy components over time with regard to race by combining ethnographic accounts with social network data collected throughout the academy and using a variety of network analytic tools. These consequences with regard to race were examined as a part of social network evolution. The academy's social arrangements did accelerate the creation of social knowledge of recruits about each other and the formation of friendship ties both within and between races. However, our results point to clear limitations to such infrastructural engineering and have implications for both recruitment to police academies and dealing with race. They shed light also on processes of homophily and group composition over time and have implications for studying social networks.     

A comparative study of social network models: Network evolution models and nodal attribute models

This paper reviews, classifies and compares recent models for social networks that have mainly been published within the physics-oriented complex networks literature. The models fall into two categories: those in which the addition of new links is dependent on the (typically local) network structure (network evolution models, NEMs), and those in which links are generated based only on nodal attributes (nodal attribute models, NAMs). An exponential random graph model (ERGM) with structural dependencies is included for comparison. We fit models from each of these categories to two empirical acquaintance networks with respect to basic network properties. We compare higher order structures in the resulting networks with those in the data, with the aim of determining which models produce the most realistic network structure with respect to degree distributions, assortativity, clustering spectra, geodesic path distributions, and community structure (subgroups with dense internal connections). We find that the nodal attribute models successfully produce assortative networks and very clear community structure. However, they generate unrealistic clustering spectra and peaked degree distributions that do not match empirical data on large social networks. On the other hand, many of the network evolution models produce degree distributions and clustering spectra that agree more closely with data. They also generate assortative networks and community structure, although often not to the same extent as in the data. The ERGM model, which turned out to be near-degenerate in the parameter region best fitting our data, produces the weakest community structure.     

Fundamental principles of network formation among preschool children

The goal of this research was to investigate the origins of social networks by examining the formation of children's peer relationships in 11 preschool classes throughout the school year. We investigated whether several fundamental processes of relationship formation were evident at this age, including reciprocity, popularity, and triadic closure effects. We expected these mechanisms to change in importance over time as the network crystallizes, allowing more complex structures to evolve from simpler ones in a process we refer to as structural cascading. We analyzed intensive longitudinal observational data of children's interactions using the SIENA actor-based model. We found evidence that reciprocity, popularity, and triadic closure all shaped the formation of preschool children's networks. The influence of reciprocity remained consistent, whereas popularity and triadic closure became increasingly important over the course of the school year. Interactions between age and endogenous network effects were non-significant, suggesting that these network formation processes were not moderated by age in this sample of young children. We discuss the implications of our longitudinal network approach and findings for the study of early network developmental processes.     

A note on the paper ‘cost range and the stable network structures’

The analysis in the paper ‘cost range and the stable network structures’ missed a stable structure —— a line. We explain its reason and reinforce the initial conclusion.     

A note on social capital and network content

As a guide to selecting name generators for social capital research, I use network data on a probability sample of heterogeneous senior managers to describe how they sort relations into kinds, and how the kinds vary in contributing to social capital. Managers sort relations on two dimensions of strength - intimacy (especially close versus distant) versus activity (frequent contact with new acquaintances versus rare contact with old friends) - and with respect to two contents - personal discussion (confiding and socializing relations) versus corporate authority (the formal authority of the boss and informal authority of essential buy-in). Comparing name generators for their construct validity as indicators of social capital, I compute network constraint from different kinds of relations, and correlate constraint with early promotion. The correlation is strong for the network of personal relations, zero for the network of authority relations, and strongest for personal and authority relations together. I close with research design recommendations for selecting name generators.     

Social context,spatial structure and social network structure

Frequently, social networks are studied in their own right with analyses devoid of contextual details. Yet contextual features – both social and spatial – can have impacts on the networks formed within them. This idea is explored with five empirical networks representing different contexts and the use of distinct modeling strategies. These strategies include network visualizations, QAP regression, exponential random graph models, blockmodeling and a combination of blockmodels with exponential random graph models within a single framework. We start with two empirical examples of networks inside organizations. The familiar Bank Wiring Room data show that the social organization (social context) and spatial arrangement of the room help account for the social relations formed there. The second example comes from a police academy where two designed arrangements, one social and one spatial, powerfully determine the relational social structures formed by recruits. The next example is an inter-organizational network that emerged as part of a response to a natural disaster where features of the improvised context helped account for the relations that formed between organizations participating in the search and rescue mission. We then consider an anthropological example of signed relations among sub-tribes in the New Guinea highlands where the physical geography is fixed. This is followed by a trading network off the Dalmatian coast where geography and physical conditions matter. Through these examples, we show that context matters by shaping the structure of networks that form and that a variety of network analytic tools can be mobilized to reveal how networks are shaped, in part, by social and spatial contexts. Implications for studying social networks are suggested.     

A note on inferences regarding network subgroups

The evidence presented in Bernard et al. (1980) does not warrant their conclusion. We comment on their lack of concern with the substance of social differentiation in the systems they use as evidence. The substance of social structure is argued to affect the scope, adequacy and power of conclusions drawn from a network analysis and is accordingly a factor to be explicitly considered in justifying those conclusions. With these ideas in mind, our reanaly sis of one system on which good data are available, ostensibly supporting the Bernard et al. conclusion, illustrates how their conclusion regarding network subgroups in that system is unwarranted     

Research note: The consequences of different methods for handling missing network data in stochastic actor based models

Although stochastic actor-based models (e.g., as implemented in the SIENA software program) are growing in popularity as a technique for estimating longitudinal network data, a relatively understudied issue is the consequence of missing network data for longitudinal analysis. We explore this issue in our research note by utilizing data from four schools in an existing dataset (the AddHealth dataset) over three time points, assessing the substantive consequences of using four different strategies for addressing missing network data. The results indicate that whereas some measures in such models are estimated relatively robustly regardless of the strategy chosen for addressing missing network data, some of the substantive conclusions will differ based on the missing data strategy chosen. These results have important implications for this burgeoning applied research area, implying that researchers should more carefully consider how they address missing data when estimating such models.     

Types of stable network structures based on exhaustive search

Based on the works of Doreian [Doreian, P., 2006. Actor network utilities and network evolution. Social Networks 28, 137–164] and Xie and Cui [Xie, F., Cui, W., 2008b. A note on the paper ‘cost range and the stable network structures’. Social Networks 30, 102–103], the paper applies exhaustive search and inductive approaches to analyze possible transitions among isomeric social networks with five vertices. A total of seven types of stable network structures are identified, which include the complete, star, chain, cycle, near-chain, near-cycle and null graphs. Then, a modified theorem for the equilibrium forms which corrects the previous work is presented.     

The evolution of the board interlock network following Sarbanes-Oxley

We examine the impact of the passage of Sarbanes-Oxley (SOX) on the evolution of the board interlock network for Fortune 300 firms during the 1998–2006 period using a stochastic actor-oriented model. Placing particular emphasis on director accountability and board independence, SOX created considerable disparity in demand and supply in the labor market for corporate directors. We examine whether the regulatory change may have led firms to draw more on socially embedded processes of board interlock partner selection such as reciprocity, transitivity, and multiplexity after SOX. We find that after the passage of SOX, a firm’s tendency to reciprocate board interlock ties has been reinforced. Similarly, firms appear to have relied more on their existing alliance partners to fill their board seats in the post-SOX period.     

Group based trajectories of network formation and dynamics

In this paper, we propose the application of a semi-parametric statistical methodology called Group-Based Developmental Trajectory Analysis to studying the dynamics of social networks. We begin with a discussion of theoretical problems in network analysis that may benefit from this approach. Next, we describe the methodology and how it can be applied to dyadic network data as well as aggregated node level data. We then demonstrate the methodology by analyzing the Newcomb Fraternity and the van de Bunt student data sets. Finally, we conclude with a discussion of potential directions for further research.     

Appropriate discounting of future utilities need not be the dictatorship of the present: A note on Chichilnisky

Positive, but non-excessive discounting of future utilities to take account of possible non-realization/survival is not the dictatorship of the present, contrary to Chichilnisky's argument which is ingenious but contains a slip due to the improper treatment of infinity. As the probability of people existing a trillion to the power of a trillion years from now is close to zero, the fact that their voice now is also close to zero should not be regarded as the dictatorship of the present. Correspondingly, Chichilnisky's criterion which gives the welfare of people in year infinity some extra weight over-and-above their due weight in accordance to the realization probability, is not acceptable. This paper is drafted during my visit to the City University of Hong Kong late in 2001 and revised during my visit to the National University of Singapore in 2002. I am particularly grateful Professors Eden Yu and Euston Quah. The motivation for writing this paper is sparked by my drafting of the theme paper on welfare economics and sustainable development, published as Ng and Wills (2002), for UNESCO and EOLSS.     

Review of the effects of Five Factor Model personality traits on network structures and perceptions of structure

We review recent research on Five Factor Model personality and social network analysis to assess how structures develop and are perceived. Extraversion and agreeableness relate consistently to personal but not workplace networks. Extraverts are more likely to seek connections, whereas agreeable individuals receive connections from others. Openness predicts network diversity and is marginally related to position when groups pursue collective goals. Conscientiousness is associated with maintaining certain personal relationships, but is strongly related to central positions in workplace networks. Neuroticism has no consistent relationship with network size or composition, and is differentially related to network positions, depending on the context.     

Omission and commission errors in network cognition and network estimation using ROC curve

Network studies on cognitive social structures collect relational data on respondents’ direct ties and their perception of ties among all other individuals in the network. When reporting their perception networks, respondents commit two types of errors, namely, omission (false negatives) and commission (false positives) errors. We first assess the relationship between these two error types, and their contributions on overall respondent accuracy. Next we propose a method for estimating networks based on perceptions of a random sample of respondents from a bounded social network, which utilizes the receiver operator characteristic curve for balancing the tradeoffs between omission and commission errors.     

A note on missing network data in the general social survey

There is very little network data missing on respondents to the 1985 General Social Survey. Missing data on relations between discussion patterns pose the greatest problem but the unknown relations are strongly associated with relations known to be weak. The association between missing and weak relations remains strong after controls for the number, strength, and nature of a respondent's discussion relations. Moreover, the association remains strong across different kinds of respondents despite significant tendencies for certain kinds of respondents to have provided incomplete network data. The implication is that the missing network data can be replaced with quantitative data indicating a weak relation.     

How stable is the core discussion network?

Researchers have paid increasing attention to the core discussion network, the set of people we turn to when discussing important matters. Because the core discussion network is theorized to be composed of people's closest ties, not fleeting acquaintances, it is expected to be largely stable, evolving slowly over the span of people's lives. However, recent studies have shown that networks are strongly affected by the contexts in which people interact with others, and as people experience life course transitions, they also often enter new contexts – school, college, work, marriage, and retirement. We ask whether, as actors enter new social contexts, the core discussion network remains stable or changes rapidly. Based on original, longitudinal, qualitative and quantitative data on the experience of first-year graduate students in three academic departments in a large university, we examine the stability of the core discussion network over the first 6 and 12 months in this new context. We test four competing hypotheses that focus on strength of ties, new opportunities, obligations, and routine activity and predict, respectively, stasis, expansion, shedding, and substitution. We find that the core discussion network changes remarkably quickly, with little or no lag, and that it appears to do so because both the obligations that people face and the routine activities they engage in are transformed by new institutional environments. Findings suggest that core discussion network may be less a “core” network than a highly contextual support network in which people are added and dropped as actors shift from environment to environment.