The role of network setting and gender in online content popularity

In this study, we explore the role of specific network structures that enhance social capital and assess the extent to which gender, social ties, and communication interaction relate to content popularity within online social networks (OSNs). Our results are based on an extensive OSN data set, containing over 100,000 members, connected by over 1.7 million links. The findings indicate that content popularity inference is more accurate when considering activity interaction among users and that network structures known as advantageous for amassing social capital in the offline environment are relevant online as well. We conclude by discussing how gender mediates the correlation between some network measures and the growth of users’ content popularity and provide a potential explanation for the emergence of gender differences.     

A concept for measuring network proximity of regions in R&D networks

This paper proposes a new measure for assessing the network proximity between aggregated units, based on disaggregated information on the network distance of actors. Specific focus is on R&D network structures between regions. We introduce a weighted version of the proximity measure, related to the idea that direct and indirect linkages carry different types of knowledge. First-order proximity arising from direct cross-regional linkages is distinguished from higher-order network proximity, resulting from indirect linkages in the R&D network. We use an macroeconomic application in which we analyse the productivity effects of R&D network spillovers across regions to illustrate the usefulness of a proximity measure for aggregated units.     

Organizational Linkages among the Inner Group of the Capitalist Class

Abstract

This study investigates the non-corporate organizational linkages among the inner group of the capitalist class, defined as those who are interlocked with three or more corporations. To the extent that persons already linked through corporate ties also are connected through common memberships in business organizations, social clubs, and other voluntary organizations, the likelihood of a national cohesive power elite is increased. The corporate data used are from the 1976 government study of the 130 major companies in the United States, controlling collectively 25 percent of all assets. The biographical data on the 66 individuals found to sit on three or more boards among these 130 companies were taken from Who's Who. Several key organizations were found where the members of the elite were especially interconnected. A cluster of 15 individuals with 13 or more common memberships within the 66 were identified as having the greatest linkages. The analysis of the number of common links for each possible pair among these 15 individuals revealed an average of 2.76. Moreover, one-third of the 15 had four links or more, with at least five persons among this inner circle, revealing the nucleus of the inner group. These data show that there is a social network, national in scope, which provides a basis for unity among leaders of the capitalist class.     

THE FAMILY TASK INTERVIEW: A TOOL FOR CLINICAL RESEARCH IN FAMILY INTERACTION

The Family Task Interview (FTI) is a multiple task interview administered by tape recorder and designed to elicit clinically relevant family interaction. The FTI has been designed to improve on previous similar instruments and a series of studies to evaluate its validity, reliability, and acceptability have been carried out. Further psychometric and practical evaluation is necessary, but results so far suggest that the FTI is a well standardized and easily administered instrument which is useful for research where assessment of family interaction using direct observation is required.     

Network inference,error, and informant (in)accuracy: a Bayesian approach

Much, if not most, social network data is derived from informant reports; past research, however, has indicated that such reports are in fact highly inaccurate representations of social interaction. In this paper, a family of hierarchical Bayesian models is developed which allows for the simultaneous inference of informant accuracy and social structure in the presence of measurement error and missing data. Posterior simulation for these models using Markov Chain Monte Carlo methods is outlined. Robustness of the models to structurally correlated error rates, implications of the Bayesian modeling framework for improved data collection strategies, and the validity of the criterion graph are also discussed.     

Hubs and Authorities in the Koch Brothers Network

The empirical focus is centered on the large social movement network created by the Koch Brothers to further their aims of transforming the US. The network was obtained by using the VOSON web crawler given a starting set of known allies of the Koch Brothers. This produced a large directed network with links between units. We propose using the idea of hubs and authorities as another way of considering the roles played by the units within this network. These roles may be more complex than has been realized. We have included an analysis of the core interests for the members of this network.     

Multiple Views of the Family and Adolescent Social Competencies

This research examined the linkages between congruence in perceptions of family functioning and adolescent competencies with a sample of 223 first‐year college students, their mothers, and their fathers. The primary goal was to explore further the nature and importance of perceptual congruence as related to adolescent social competencies with a more informative analytic strategy than has been used in most past research (one that controls for individual perceptions of family members and takes into account direction of differences among family members), and with more comprehensive, multimethod assessments of adolescent competencies. Our congruence analyses portrayed a more complex picture of congruence and divergence than has emerged from previous studies, and highlight the importance of examining interaction patterns in future research. It is noteworthy, however, that individual perceptions of family members were more important than was congruence in relation to adolescent social competencies. The possibility that congruence effects may be more apparent when the focus is on more specific rather than global measures and on developmental as well as family interaction processes is suggested.     

Research Attitudes and Their Correlates Among Undergraduate Social Work Students

Efficient and practical means of disseminating research to social workers are needed. The authors examined how 10 social work and 10 other helping profession association websites used their sites to disseminate research to their members. A rubric was used to rate the websites in 4 domains: (1) promotion, (2) accessibility, (3) dissemination, and (4) linkages to credible research information. Findings reveal that online dissemination of research by these professional associations is lacking. Recommendations include use of a prominent research tab on the homepage, inclusion of research syntheses, and links to additional research resources. Professional associations must improve their websites to become the foremost portals by which social workers stay informed of the most current research in their respective practice areas.     

Measuring social networks cross-culturally

This paper explores the reliability and validity of a cross-cultural survey approach to network measurement using data from two ethnic groups in rural West Africa. Over a 2-week test-retest period, no significant differences in network size were detected. Network composition was less stable over the same period, particularly among peripheral versus core network members. Comparisons with support networks identified through lifecycle interviews and 24 h recall support the construct validity of the survey approach in both ethnic groups.     

Using Social Network Analysis to Explore Social Movements: A Relational Approach

This paper uses a ‘relational’ approach to network analysis to demonstrate the linkages between different types of environmental organizations in London. A ‘relational’ approach was used to avoid problems associated with ‘positional’ approaches such as structural determinism, subjectively defined and misleadingly labelled blocks of ‘approximately’ equivalent actors, and reification of the action/issue basis of networks. The paper also explores definitions of social/environmental movements. Whilst broadly agreeing with Diani's consensual definition of a social movement, it argues that we need to be much more precise about the type and intensity of networking required; it must be more than informal or cursory, and should bind individuals and organizations into collaborative networks. Evidence from a survey of 149 environmental organizations and qualitative interviews with key campaigners suggests that whilst many organizations might share information, it is often stockpiled or ignored, hardly creating the kinds of network links that might lead to shared movement identity. The kinds of links that do bind movements are collaborative. In practice, in the environmental movement in London, conservationists tend neither to share information nor to engage in the collective action events of reformist or radical organizations, suggesting that conservationists should perhaps not be considered part of the movement.     

Covariate-defined latent space random effects model

Latent factor models are a useful and intuitive class of models; one limitation is their inability to predict links in a dynamic network. We propose a latent space random effects model with a covariate-defined social space, where the social space is a linear combination of the covariates as estimated by an MCMC algorithm. The model allows for the prediction of links in a network; it also provides an interpretable framework to explain why people connect. We fit the model using the Adolescent Health Network dataset and three simulated networks to illustrate its effectiveness in recognizing patterns in the data.     

Exploring How National Politics Influences the Outcome of Intergroup Contact among Muslim Minority Members

This article adds to the existing research in intergroup contact among ethnic minority members by hypothesizing that national political debate has the capacity to enhance the positive outcomes of cross‐group interaction. Analyses show that the capacity of intergroup contact to reduce prejudice toward majority members is disproportionately stronger among Muslims than among non‐Muslim minority members. Specifically, at the time of data collection, the two categories—Muslims and majority members—were highly salient in the public debate, whereas the non‐Muslim minority member category was not primed as a contrast to the majority culture. The political debate most likely stimulated Muslims to generalize their positive contact experiences to the entire majority group. The analysis contributes to the theoretical refinement of the so‐called categorization model by focusing on politically induced reactions among contacted ethnic minority members toward majority members. The analysis utilizes a tailor‐made national sample (fielded during the Mohammad Cartoon Crisis in 2006) among ethnic minority members in Denmark (N  = 3,272).     

A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models

The statistical modeling of social network data is difficult due to the complex dependence structure of the tie variables. Statistical exponential families of distributions provide a flexible way to model such dependence. They enable the statistical characteristics of the network to be encapsulated within an exponential family random graph (ERG) model. For a long time, however, likelihood-based estimation was only feasible for ERG models assuming dyad independence. For more realistic and complex models inference has been based on the pseudo-likelihood. Recent advances in computational methods have made likelihood-based inference practical, and comparison of the different estimators possible.     

Dynamic exchange networks

Considering the theoretical and empirical untenability of static exchange networks, researchers have asked how exchange outcomes change when links are added or deleted. The present paper assesses the validity of seemingly sensible propositions concerning the effects of adding and deleting a link on (i) the payoffs of the actors in the link, (ii) the payoffs of actors in neighboring links and (iii) the variance of payoffs in the exchange network. The propositions were examined by applying expected value theory (EVT) to all 13,597 networks up to size 8. All propositions were falsified. Some falsifications of propositions could be attributed to EVTs prediction that actors use sub-optimal exchange relations. Since other well-known theories of exchange, like power-dependence theory and network exchange theory, also predict that actors use sub-optimal relations, these results are robust to selection of the theory of exchange.     

Revisiting the accuracy problem in network analysis using a unique dataset

A series of papers published by Bernard and colleagues in the late 1970s and early 1980s, dubbed the “accuracy studies,” called into the question the validity of self-reported perceived communication in the study of networks, showing that such reports explain only about 20 % of the variance in directly observed communication. Questions remain about how well the kinds of organizations studied reflect typical formal organizations, the studies’ short observation periods, and manual observation methods. This study revisits the accuracy studies using a unique dataset comprising 144 weeks of network surveys and machine classification of 7,000 h of audio recordings to measure observable communication in a software engineering unit employing 54 people. Results show that correlations between perceived and observed communication over the weeks studied have a lower average than that reported in the accuracy studies but vary considerably from week to week. It also replicates results of earlier research showing that participants tend to overreport communication when they perceive a strong structural relationship to the alters they are rating. This study solidifies our knowledge about network self-reports using a stronger data foundation than prior research employed. Its results, along with the previous research, suggest that perceived communication is not so much a flawed measure of observable communication as it is a related, yet distinct phenomenon. This highlights the need for developments in theory and modeling that articulate the relationship between perceived and observed communication, and Network Reticulation Theory is suggested as a viable approach.     

For Refugees,the Road to Employment in the United States Is Paved With Workable Uncertainties and Controversies

Drawing on data—including survey responses, interviews, documents, and participant observation—collected during a 26‐month ethnography of refugees in a northeastern U.S. city, I examine how recently arrived refugees create and access new employment opportunities. I utilize actor‐network theory (ANT) to examine refugees' linkages as emerging, temporal, and fluid. I empirically trace the drawing together of, and interaction among, individual refugees, formal organizations, new cultural ideas, and a myriad of material objects. I examine the connections between the uncertainties about actors, action, and agency that point to the need to understand society as sociomaterial networks. I analyze the controversies that are deployed in an emerging assemblage as the refugees entered the paid workforce in the United States. I am guided by a broad question: How are meaning, knowledge, and facts that come to make up a network actually made, maintained, remade, and, sometimes, undone? I demonstrate that putting assemblage to work offers insights into the ways in which heterogeneous elements come together in often unanticipated ways to create stable, even if temporary, employment networks for refugees in the United States.     

Privacy and confidentiality considerations for collecting HIV risk network data among men who have sex with men and implications for constructing valid risk networks

Studies aiming to construct risk networks have historically collected network members' names, demographic characteristics and relational data (i.e., type, strength, duration, frequency of interaction, and HIV-related risk behaviors between the pair). Due to difficulties in constructing risk networks stemming from partner anonymity and the use of nicknames, some studies also collect network members’ screen names, phone numbers, physical attributes, and scars/tattoos to assist with entity resolution. In-depth interviews with 20 men who have sex with men and transgender women in Kentucky assessed privacy/confidentiality concerns as well as accuracy/recall issues associated with providing these details. Most preferred providing alters’ nicknames/first names only or a first name with the first letter of the last name. Many perceived screen names, phone numbers, and scars/tattoos to be too personal/identifying. Willingness to provide more detailed information varied by relationship type/strength, which could influence the validity of the resulting network.     

Ranking terrorists in networks: A sensitivity analysis of Al Qaeda's 9/11 attack

All over the world, intelligence services are collecting data concerning possible terrorist threats. This information is usually transformed into network structures in which the nodes represent the individuals in the data set and the links possible connections between these individuals. Unfortunately, it is nearly impossible to keep track of all individuals in the resulting complex network. Therefore, Lindelauf et al. (2013) introduced a methodology that ranks terrorists in a network. The rankings that result from this methodology can be used as a decision support system to efficiently allocate the scarce surveillance means of intelligence agencies. Moreover, usage of these rankings can improve the quality of surveillance which can in turn lead to prevention of attacks or destabilization of the networks under surveillance.The methodology introduced by Lindelauf et al. (2013) is based on a game theoretic centrality measure, which is innovative in the sense that it takes into account not only the structure of the network but also individual and coalitional characteristics of the members of the network. In this paper we elaborate on this methodology by introducing a new game theoretic centrality measure that better takes into account the operational strength of connected subnetworks.Moreover, we perform a sensitivity analysis on the rankings derived from this new centrality measure for the case of Al Qaeda's 9/11 attack. In this sensitivity analysis we consider firstly the possible additional information available about members of the network, secondly, variations in relational strength and, finally, the absence or presence of a small percentage of links in the network. We also introduce a case specific method to compare the different rankings that result from the sensitivity analysis and show that the new centrality measure is robust to small changes in the data.     

Shared responsibility and network collaboration in caregiving

Communal coping may benefit caregivers, but most communal coping research focuses on dyads. Using an egocentric network design, we examine caregivers’ we-talk—a linguistic marker of shared responsibility—and caregiver reports of 1) network member involvement in collaborative care roles and 2) met/unmet expectations across typically developing and rare disease contexts. We-talk was linked to involvement in direct care and support, but links of we-talk to decision-making varied based on network member closeness; we-talk was linked to meeting expectations for decision-making only. There were no differences across context, suggesting shared responsibility is linked to collaborative roles across caregiving contexts.     

INDICES OF ROBUSTNESS FOR SAMPLE REPRESENTATION

Social scientists are rarely able to gather data from the full range of contexts to which they hope to generalize ( Shadish, Cook, and Campbell 2002 ). Here we suggest that debates about the generality of causal inferences in the social sciences can be informed by quantifying the conditions necessary to invalidate an inference. We begin by differentiating the target population into two subpopulations: a potentially observed subpopulation from which all of a sample is drawn and a potentially unobserved subpopulation from which no members of the sample are drawn but which is part of the population to which policymakers seek to generalize. We then quantify the robustness of an inference in terms of the conditions necessary to invalidate an inference if cases from the potentially unobserved subpopulation were included in the sample. We apply the indices to inferences regarding the positive effect of small classes on achievement from the Tennessee class size study and then consider the breadth of external validity. We use the statistical test for whether there is a difference in effects between two subpopulations as a baseline to evaluate robustness, and we consider a Bayesian motivation for the indices and compare the use of the indices with other procedures. In the discussion we emphasize the value of quantifying robustness, consider the value of different quantitative thresholds, and conclude by extending a metaphor linking statistical and causal inferences.