A note on actor network utilities and network evolution

The corrections provided by Xie and Cui [Xie, F., Cui, W., in press. Cost range and network structures. Social Networks, 30] to one of the theorems provided by Doreian [Doreian, P., 2006. Actor network utilities and network evolution. Social Networks, 28, 137–164] are both necessary and helpful. Accepting these corrections, and linking them more closely to the work of Hummon [Hummon, N.P., 2000. Utility and dynamic social networks. Social Networks, 22, 221–249], leads to some additional suggestions which, together with a restatement of some earlier results, help set the foundations for future work in this area.     

Geographical variability and network structure

In this paper, we explore the potential implications of geographical variability for the structure of social networks. Beginning with some basic simplifying assumptions, we derive a number of ways in which local network structure should be expected to vary across a region whose population is unevenly distributed. To examine the manner in which these effects would be expected to manifest given realistic population distributions, we then perform an exploratory simulation study that examines the features of large-scale interpersonal networks generated using block-level data from the 2000 U.S. Census. Using a stratified sample of micropolitan and metropolitan areas with populations ranging from approximately 1000 to 1,000,000 persons, we extrapolatively simulate network structure using spatial network models calibrated to two fairly proximate social relations. From this sample of simulated networks, we examine the effect of both within-location and between-location heterogeneity on a variety of structural properties. As we demonstrate, geographical variability produces large and distinctive features in the “social fabric” that overlies it; at the same time, however, many aggregate network properties can be fairly well-predicted from relatively simple spatial demographic variables. The impact of geographical variability is thus predicted to depend substantially on the type of network property being assessed, and on the spatial scale involved.     

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.     

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.     

天津高速铁路线网规划的演进和探析

改革开放30多年来,国民经济的持续发展促进了交通运输需求的快速增长,城市之间的中长距离客流交换日益频繁。2008年8月1日,我国第一条具有世界一流水平、最高运营速度350公里／小时的高速铁路——京津城际客运专线的正式通车运营标志着铁路高速化时代的到来。根据国家《中长期铁路网规划》,至2020年“四纵四横”的高速铁路主骨架与提速的既有铁路将共同形成共计5万公里以上的快速铁路客运线网,     

Network structure,strategy evolution,and the game of Chicken

Cellular automata – lattice-like grids of interlinked cells – can be used to study system evolution. The cells are occupied by disputants with differing strategic interaction rules. After interacting, each disputant either retains its strategy or adopts that of a neighbor, depending on relative strategy success. In this article, we use networks to answer questions about strategy evolution in the game of Chicken. We identify the nodes of a network with cells of an automaton and consider nodes adjacent if they are neighboring cells in the automaton, allowing us to determine structural influences of strategy evolution.     

Event sequences as generators of social network evolution

The argument presented in this paper is that one fruitful approach to the study of social network evolution takes the form of examining event sequences as generating mechanisms. Evidence for this comes from two empirical studies of structural balance theory and one simulation study of balance theoretic processes. Four views of causality—system, statistical (predictive), mechanism and algorithmic—are briefly contrasted and then examined with structural balance theory in mind. The conventional statement of the theory turns out to be under specified and inattentive to alternative mechanisms that can generate signed networks through time. Empirical studies of structural balance are limited with regard to the kinds of data that are usually collected. Proposals for studying the generation of signed networks through event sequences while being attentive to structural balance ideas are presented.     

Social network structure and the trade-off between social utility and economic performance

We put forward a computational multi-agent model capturing the impact of social network structure on individuals’ social trust, willingness to cooperate, social utility and economic performance. Social network structure is modeled as four distinct social capital dimensions: degree, centrality, bridging and bonding social capital. Model setup draws from socio-economic theory and empirical findings based on our novel survey dataset. Results include aggregate-level comparative statics and individual-level correlations. We find, inter alia, that societies that either are better connected, exhibit a lower frequency of local cliques, or have a smaller share of family-based cliques, record relatively better aggregate economic performance. As long as family ties are sufficiently valuable, there is a trade-off between aggregate social utility and economic performance, and small world networks are then socially optimal. We also find that in dense networks and trustful societies, there is a trade-off between individual social utility and economic performance; otherwise both outcomes are positively correlated in the cross section.     

Predicting the structure of a communications network from recalled data

In a series of papers on informant accuracy in social network data, Bernard, Killworth, and more recently, Sailer, have concluded that “what people say, despite their presumed good intentions, bears no useful resemblance to their behavior” (Bernard, Killworth, and Sailer 1982: 63). In this paper we reanalyze one of the data sets (the technical group) utilized by Bernard, Killworth and Sailer in arriving at their conclusions. Unlike Bernard et al. we find that the observed behavior data corresponds closely to the recalled data. Using different methods of analysis we find that the verbal recall data can be used to predict structural aspects of the observed data. Two major findings emerge from our analysis: first, the more similarly two people judge the communication pattern of others, the more they interact with each other, and, second, the more two people share accurate knowledge of others, the more they interact with each other. Implications of our findings for the assertions of Bernard, Killworth and Sailer are discussed.     

The evolution of structural resilience of global oil and gas resources trade network

This paper establishes anetwork resilience evaluation framework of the global oil and gas resourcetrade network in 2010, 2015 and 2020. The results are as follows: The links of the oil trade network present a gradually shrinking trend, and the gas tradenetwork presents a trend of close connection first and then reduced. In termsof network density, network centrality, network connectivity and network size, the structural resilience of the oil and gas resource trade network displays ashrinking trend, and the gas trade network is superior. Concerninginvulnerability and recovery, the resilience of the oil trade network issuperior to the natural gas trade network. In simulated attacks, the oil tradenetwork reveals a higher resilience towards intentional attacks, and the gastrade network shows a higher resilience towards random attacks. The Strait ofHormuz and the Strait of Malacca are critical chokepoints in the networks.     

The structure and vulnerability of a drug trafficking collaboration network

Prior research has established that collaboration networks exhibit heavy-tailed degree distributions, assortative degree mixing, and large clustering coefficients. Using court record data, we assess these properties in a collaboration network among heroin traffickers. Consistent with prior research, we find an exponential degree distribution and strong local clustering. However, the traffickers mix dissortatively by degree rather than assortatively. Using a graph sampling method, we show that a consequence of dissortative mixing is that targeted vertex removals have a greater impact on the connectivity and cohesion of the trafficking network. We also note the importance of degree mixing for characterizing and identifying topological weaknesses.     

Protecting ecosystems: network structure and social capital mobilization

The research reported here explores a community that amassedsocial capital in effective and diverse ways, enabling it tofight a corporate giant and protect critical, large watersheds.We explore how the dynamic interaction between network formationand network structure augmented community social capital, particularlybridging, for increased access to human and economic capital.Network structure(s) can create enabling conditions for themobilization of social capital within communities and for peopleto feel empowered to act. The research suggests that there isan opportunity for policy-makers to learn what kinds of policiescan enhance or destroy existing social capital in a community.     

Information communities: The network structure of communication

This study puts forward a variable clique overlap model for identifying information communities, or potentially overlapping subgroups of network actors among whom reinforced independent links ensure efficient communication. We posit that the average intensity of communication between related individuals in information communities is greater than in other areas of the network. Empirical tests show that the variable clique overlap model is indeed more effective in identifying groups of individuals that have strong internal relationships in communication networks relative to prior cohesive subgroup models; the pathways generated by such an arrangement of connections are particularly robust against disruptions of information transmission. Our findings extend the scope of network closure effects proposed by other researchers working with communication networks using social network methods and approaches, a tradition which emphasizes ties between organizations, groups, individuals, and the external environment.     

Exploratory social-spatial network analysis of global migration structure

At the global level, international migration can be considered as a network of migration exchanges between different countries. Employing an exploratory network analysis of the international migration structure, the present paper examines the structural characteristics of this network and the status of the countries. The analysis is done using the socio-spatial approach. Results show that as the severity of network ties grow, the number of ties reduce significantly and ties are asymmetric. Most of the migrations in the international migration structure have also taken place outside the near and neighboring countries. The network analysis showed two migration patterns of "International Migratory Highways" and "Migratory Clusters". In the first migration pattern, migrations are largely asymmetric and towards the major centers of immigration, while in the second one, migrations are mostly symmetric and within specific geographical areas.     

Creating the thin blue line: Social network evolution within a police academy

Whenever major schisms between police and communities come to public attention, there are always passionate calls for an increased emphasis on - and improvement of - police training. This rhetoric is so common that police leaders joke that there is no societal problem so big that it can’t be fixed by better police training. Still, professional socialization in law enforcement remains an important topic with a great deal of resources being devoted to developing initiatives and augmenting existing curricula. This training comes in many forms including learning the nuts and bolts of many legal processes and acquiring the practical skills for law enforcement. However, beyond this, there is a socialization process with multiple facets including the development of solidarity and trust among a cohort of recruits. We attempt to understand the basic mechanisms of network creation in police academies as the foundation of the socialization processes within them. By focusing on these network mechanisms underlying the establishment of the ‘Thin Blue Line’, we offer an understanding of the underlying social processes foundational for the transmission of police culture. In short, we think the recruit network structure functions as a vehicle for cultural transmission within police academies.     

Ego centered social network and relationship quality: linking attachment security and relational models to network structure

According to Dunbar’s social brain hypothesis, brain capacity puts a limit on the size of social network in humans. At the same time, emotional-cognitive systems such as attachment and different relational models (Fiske, 1991) may also act as driving forces behind network structure underlying relationship quality of the various ego-centered layers. The aim of our study was to examine how these cognitive systems may contribute to network organization.We examined the two inner layers of the ego-network in 274 volunteers, the support and sympathy groups, as well as close family members in comparison to friends within the support group, in terms of attachment security and underlying relational models.     

Psychological predispositions and network structure: The relationship between individual predispositions,structural holes and network closure

We examine the effect of individual psychological differences on network structures, proposing several hypotheses about how individual differences might predispose actors to structure their social environment by seeking network closure or by sustaining structural holes. We introduce a new triad census method to examine personal networks of strong and weak ties. For 125 egocentric networks we correlated the triad census results with several extensively researched psychological instruments. The triad census reduced to three principal components, describing central aspects of strength-of-weak-ties and structural holes theories. Psychological predispositions explained a significant proportion of the variance in each of these components. Our results suggest that people who see themselves vulnerable to external forces tend to inhabit closed networks of weak connections. On the other hand, people who seek to keep their strong tie partners apart, and thereby bridge structural holes, tend to be individualists, to believe that they control the events in their lives, and to have higher levels of neuroticism. Finally, people with strong network closure and “weak” structural holes (as with the “strength of weak ties”) tend to categorize themselves and others in terms of group memberships. They also tend to be more extraverted and less individualistic.     

Organizational status growth and structure: An alliance network analysis

Considering the status system emerging from a structure of corporate affiliations, we examine how alliance patterns among firms affect their changing organizational statuses and the structural development of the status system itself. Firm status is conceptually grounded in sociological theories of status and network analysis. The empirical setting we investigate is the network of alliances among firms in the Global Information Sector. The results indicate a negative effect of initial firm status on the growth rate of individual status, which is associated with the different patterns of alliance affiliations among firms with different status levels. Affiliation patterns also affect the extent of variation in the gap between status strata and firm mobility along the status hierarchy. The results highlight the importance of understanding the structural aspects underlying firm status attainment.