Gender bias in the classroom: A network study on self and peer ability attribution

Stereotypes can contribute to the gender gap in STEM by shaping people’s expectations on their own and others’ performance. When gender is salient, expectations on task performance might reflect gender constructs even when information on individual abilities is available. We tested this hypothesis in a network study on students from ten high school classes in Milan, Italy. We asked the students to choose the four best candidates from their classmates for three hypothetical inter-class competitions in reading, math, and science. Results showed that females were more likely to be nominated for the reading competition but less likely for science. We did not find any statistically significant results for the math competition. We also found that female students were less likely to nominate themselves for any competition, regardless of the subject, even controlling for their own performance and self-concept.     

A comparison of estimators for the network autocorrelation model based on observed social networks

Network autocorrelation models (NAMs) are widely used to study a response variable of interest among subjects embedded within a network. Although the NAM is highly useful for studying such networked observational units, several simulation studies have raised concerns about point estimation. Specifically, these studies have consistently demonstrated a negative bias of maximum likelihood estimators (MLEs) of the network effect parameter. However, in order to gain a practical understanding of point estimation in the NAM, these findings need to be expanded in three important ways. First, these simulation studies are based on relatively simple network generative models rather than observed networks, thereby leaving as an open question how realistic network topologies may affect point estimation in practice. Second, although there has been strong work done in developing two-stage least squares estimators as well as Bayesian estimators, only the MLE has received extensive attention in the literature, thus leaving practitioners in question as to best practices. Third, the performance of these estimators need to be compared using both bias and variance, as well as the coverage rate of each estimator's corresponding confidence or credible interval. In this paper we describe a simulation study which aims to overcome these shortcomings in the following way. We first fit real social networks using the exponential random graph model and used the Bayesian predictive posterior distribution to generate networks with realistic topologies. We then compared the performance of the three different estimators mentioned above.     

Social context and network formation: An experimental study

Recently, there has been increasing interest in determining which social network structures emerge as a consequence of the conscious actions of actors. Motivated by the belief that “networks matter” in reaching personal objectives, it is a natural assumption that actors try to optimize their network position. Starting from the notion that an optimal network position depends on the social context, we examine how actors change their networks to reach better positions in various contexts. Distinguishing between three social contexts (a neutral context, a context in which closed triads are costly, and a context in which closed triads are beneficial), theoretical results predict that emerging networks are contingent on the incentives that are present in these contexts. Experiments are used to test whether networks that are theoretically predicted to be stable are also stable experimentally. We find that emerging networks correspond to a large extent with the predicted networks. Consequently, they are contingent on the incentives present in various social contexts. In addition, we find that subjects tend to form specific stable networks with a higher probability than predicted, namely, efficient networks and networks in which everyone is equally well off.     

An agent-based model of network effects on tax compliance and evasion

Agent-based models are flexible analytical tools suitable for exploring and understanding complex systems such as tax compliance and evasion. The agent-based model created in this research builds upon two other agent-based models of tax evasion, the Korobow et al., 2007, Hokamp and Pickhardt, 2010 models. The model utilizes their rules for taxpayer behavior and apprehension of tax evaders in order to test the effects of network topologies in the propagation of evasive behavior. Findings include that network structures have a significant impact on the dynamics of tax compliance, demonstrating that taxpayers are more likely to declare all their income in networks with higher levels of centrality across the agents, especially when faced with large penalties proportional to their incomes. These results suggest that network structures should be chosen selectively when modeling tax compliance, as different topologies yield different results. Additionally, this research analyzed the special case of a power law distribution and found that targeting highly interconnected individuals resulted in a lower mean gross tax rate than targeting disconnected individuals, due to the penalties inflating the mean gross tax rate in the latter case.     

Conflict dynamics in collaborative knowledge production. A study of network gatekeeping on Wikipedia

Digitalization has fundamentally changed gatekeeping by allowing users to participate in processes of information control. We study gatekeeping on Wikipedia by analyzing networks of deletions among editors. Factors considered to explain the emergence of these networks are editors’ information production capability, their range of activity, their communicative ties, their geographical location, and their past interactions. Relying on relational event models, we find that the observed gatekeeping processes are not only shaped by the factors related to an editor’s standing in the community, but also to a certain extent by their attribution to content-related groups and some forms of past interactions.     

Adolescent aggression: The role of peer group status motives,peer aggression,and group characteristics

Recent studies of youth aggression have emphasized the role of network-based peer influence processes. Other scholars have suggested that aggression is often motivated by status concerns. We integrate these two veins of research by considering the effects of peer status motivations on subsequent adolescent aggression, net of their own status motivations, prior aggression, and peer behavior. We also explore different levels at which peer effects may occur, considering the effects of reciprocated and unreciprocated friendships as well as larger, meso-level peer groups. We anticipate that peer group effects are magnified by both size and boundedness as measured by Freeman's (1972) segregation index. We find that, net of the adolescent's aggression at time 1, both the aggressive behaviors and the status valuations of friends independently increase the likelihood of aggression at time 2, 6 months later. The aggressive behavior of friends who do not reciprocate the adolescent's friendship nomination has particular impact. The average status valuation of peer groups increases their members’ likelihood of aggression, even after controlling for their own attitudes about status, their friends’ attitudes, and their friends’ aggressive behavior. This effect is magnified in large groups and groups with high Freeman segregation scores.     

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.     

Corporate competition: A self-organized network

A substantial number of studies have extended the work on universal properties in physical systems to complex networks in social, biological, and technological systems. In this paper, we present a complex networks perspective on interfirm organizational networks by mapping, analyzing and modeling the spatial structure of a large interfirm competition network across a variety of sectors and industries within the United States. We propose two micro-dynamic models that are able to reproduce empirically observed characteristics of competition networks as a natural outcome of a minimal set of general mechanisms governing the formation of competition networks. Both models, which utilize different approaches yet apply common principles to network formation give comparable results. There is an asymmetry between companies that are considered competitors, and companies that consider others as their competitors. All companies only consider a small number of other companies as competitors; however, there are a few companies that are considered as competitors by many others. Geographically, the density of corporate headquarters strongly correlates with local population density, and the probability two firms are competitors declines with geographic distance. We construct these properties by growing a corporate network with competitive links using random incorporations modulated by population density and geographic distance. Our new analysis, methodology and empirical results are relevant to various phenomena of social and market behavior, and have implications to research fields such as economic geography, economic sociology, and regional economic development.     

Producing public goods in networks: Some effects of social comparison and endogenous network change

As actors participate in the production of public goods, processes of social comparison may affect the decisions about the individual contributions as well as the endogenously changing structure of an underlying social network. This leads to the transformation of an ordinary n-player Prisoner's Dilemma of collective action into an n-player coordination game. The paper uses agent-based simulations to trace the formation of public goods while varying network characteristics, such as density, segregation, or the strength of relationships. Additionally, the usage of both a forward- and a backward-looking agent model shows possible implications of different assumptions about the actors’ decision making.     

Attitude and peer influences on adolescent substance use: the moderating effect of age,sex, and substance

Many studies have suggested the importance of peer influence and personal attitudes (e.g., expectancies, resistance self-efficacy, and perceived harm) in predicting adolescent use of illegal substances. The present study examined these variables in relation to self-reported use of alcohol, cigarettes, and marijuana for 213 younger adolescents (12-15 years old) and 219 older adolescents (18-22 years old). A series of logistic regressions was performed to assess variables relating to use of each substance by age group and gender. Friends' use was significantly related to substance use for both age groups, both sexes, and all substances examined in this study. Perceived harm was not significantly related to use for any group. Finally, outcome expectancies and resistance self-efficacy were differentially related to use depending on age, gender, and substance. The implications of these findings for prevention programming and future research are also discussed.     

Social workers' assessments of needs and interventions for adolescents with substance misuse problems,criminal behaviour and mental health difficulties: a vignette study

The aim of the current vignette study was to examine how social workers assess adolescents with substance misuse problems, criminal behaviour and mental health difficulties, and how they make decisions about treatment interventions to reduce these problems. Earlier research has shown lack of knowledge concerning factors and processes that govern assessments and decisions in social work practice. In this anonymously administered survey, social workers in Stockholm, Sweden, were invited to assess fictitious youth issues. We found that social workers recognise the problems and needs of young people, but that they find it harder to link needs to evidence-based interventions. Also, there is a tendency to overrate alleged non-serious problems in the vignettes. We conclude that there is a need for increased knowledge about evidence-based methods and more structured procedures to broaden the basis for decisions.     

Predictors and outcomes of social network compositions: A compositional structural equation modeling approach

Proportions of a total, including social network compositions (proportions of partner, family, friends, etc.) lie in a restricted space, which challenges statistical analysis. Network compositions can be both dependent and explanatory variables and are usually measured with error by survey instruments. Structural equation models make it possible to correct measurement error bias. Coenders et al. (2011) fitted a factor analysis model to transformed network compositions. In this article, we use another transformation called an isometric log-ratio and we extend the model to include predictors and outcomes. The findings and hypotheses in the literature can be reformulated with isometric log-ratios in a more interpretable manner. For instance, we find relationships of gender with partner support, of education and extraversion with friend support, and of family support with tie multiplexity and closeness.     

A cross-national study on adolescent substance use: Intentions,peer substance use,and parent-adolescent communication

This longitudinal two-wave cross-national study investigated whether intentions, friends' substance use, and parent-adolescent substance-use specific communication predict adolescent alcohol and cannabis use 1 year later, while estimating reversed links. The temporal order between these two substances was also examined. We used multi-group cross-lagged panel modeling on data from 2 ethnically and socioeconomically diverse samples: Sint Maarten (N = 350; M_age = 14.19) and the Netherlands (N = 602; M_age = 13.50). Results showed that in the Netherlands, cannabis use predicts more subsequent problems (alcohol use, intention to use cannabis, and affiliation with cannabis-using friends). But for Sint Maarten, alcohol use predicts more subsequent problems (cannabis use, intention to use alcohol, and affiliation with alcohol-using friends). These opposing results demonstrate that caution is warranted when generalizing results across countries.     

Bring publics back into networked public relations research: A dual-projection approach for network ecology

This essay critiques the absence of publics in networked public relations research, and proposes the dual-projection approach as a solution to simplify and analyze the multi-mode public relations network ecology (Yang & Taylor, 2015). Compared to most previous studies that employ organization-centric networks where ties stand for hyperlinks, collaborations, or coalitions, the new approach projects organization-public relationships and public-public relationships onto interorganizational ties. By doing so, it (1) brings publics back into networked public relations research; (2) presents organizations and publics—the two most important subjects of public relations research—equally in the same network, (3) drives literature further away from a dyadic view of relationship management, and (4) constitutes one of the first techniques that can analyze direct and timely consequences of organziation-public relationships in the network ecology. To demonstrate the new approach, the network of publics overlap is introduced and applied to US-based LGBTQ advocacy groups. The essay also discusses the theoretical inquiries needed to further dual-projection networks, and invites scholars to create novel ways to incorporate publics into their network studies using dual projection.     

A network centrality bias: Central individuals in workplace networks have more supportive coworkers

Combining the results of two empirical studies, we investigate the role of alters’ motivation in explaining change in ego’s network position over time. People high in communal motives, who are prone to supportive and altruistic behavior in their interactions with others as a way to gain social acceptance, prefer to establish ties with co-workers occupying central positions in organizational social networks. This effect results in a systematic network centrality bias: The personal network of central individuals (individuals with many incoming ties from colleagues) is more likely to contain more supportive and altruistic people than the personal network of individuals who are less central (individuals with fewer incoming ties). This result opens the door to the possibility that the effects of centrality so frequently documented in empirical studies may be due, at least in part, to characteristics of the alters in an ego’s personal community, rather than to egos themselves. Our findings invite further empirical research on how alters’ motives affect the returns that people can reap from their personal networks in organizations.     

New voices in social work: an explorative study of female Turkish and Moroccan-Dutch professionals in social work in the Netherlands

In social work, the participation of Turkish and Moroccan-Dutch professionals, second and third generation migrant women from a Muslim background, is increasing. In this participative qualitative inquiry, new professionals were actively involved as co-researchers, doing research with peers from the same background. The question addressed is how these professionals deal with identity tensions and if they find positive sources of identification in social work. The new professionals claim a positive identity, connected to what they consider their strength and in particular their faith and ‘otherness’. At the same time, this increases their vulnerability, in a context in which Islam by some is considered a threat to society. The importance of a supportive professional social work identity is advocated.     

Accusation and confession discrepancies in bullying: Dual-perspective networks and individual-level attributes

Previous research on bullying implicitly assumes that individuals agree on who bullies whom and whom is bullied by who. We analyse dual-perspective networks from 96 school-classes in Germany, where adolescents were asked both whom they bully (confession network) and who bullies them (accusation network). Drawing from goal framing theory we explicitly examine discrepancies in the subjective perception of bullying, demonstrating that the majority of accusations have no corresponding confessions, and vice versa. There are more confessions than accusations overall. Furthermore, we investigate how individual-level attributes are associated with these discrepancies. Our study indicates that analyses of bullying relationships, as well as social networks in general, should account for relational discrepancies resulting from individuals’ subjective perceptions of social behaviour.     

Weight matrices for social influence analysis: An investigation of measurement errors and their effect on model identification and estimation quality

Weight matrices, such as used in network autocorrelation models, are useful to investigate social influence processes. The objective of this paper is to investigate a key topic that has received relatively little attention in previous research, namely the issues that arise when observational limitations lead to measurement errors in these weight matrices. Measurement errors are investigated from two perspectives: when relevant ties are omitted, and when irrelevant ties are erroneously included as part of the matrix. The paper first shows analytically that these two situations result in biased estimates. Next, a simulation experiment provides evidence of the effect of erroneously coding the weight matrix on model performance and the ability of a network autocorrelation test to identify social influence effects. The results suggest that depending on the level of autocorrelation and the topology attributes of the underlying matrix, there is a window of opportunity to identify and model social influence processes even in situations where the ties in a matrix cannot be accurately observed.     

Peer violence in adolescent residential care: A qualitative examination of contextual and peer factors

This research examined the way contextual and peer factors influence peer violence in adolescent residential care. One hundred and twenty residents aged 11–21 from 20 residential care facilities participated in 20 focus groups about peer violence in care. The results demonstrated that four, mutually interrelated themes, contributed to explanations of violence amongst residents: 1) residential peer culture; 2) vulnerability at the beginning of institutionalization; 3) deprivation, stigmatization and frustration; and 4) poor relationship with staff. The results are discussed with reference to the existing residential care and prison-based research on bullying and peer violence and a number of research and policy recommendations are provided.     

Leadership and contagion by COVID-19 among residence hall students: A social network analysis approach

University students have changed their behaviour due to the COVID-19 pandemic. In this paper, we describe the characteristics of PCR+ and PCR- nodes, analyse the structure, and relate the structure of student leaders to pandemic contagion as determined by PCR+ in 93 residential university students. Leadership comes from the male students of social science degrees who have PCR +, with an eigenvector centrality structure, β-centrality, and who are part of the bow-tie structure. There was a significant difference in β-centrality between leaders and non-leaders and in β-centrality between PCR+ and non-leaders. Leading nodes were part of the bow-tie structure. MR-QAP results show how residence and scientific branch were the most important factors in network formation. Therefore, university leaders should consider influential leaders, as they are vectors for disseminating both positive and negative outcomes.