Neighborhoods in the Network Society the e-Neighbors study

This study examines whether the Internet is increasingly a part of everyday neighborhood interactions, and in what specific contexts Internet use affords the formation of local social ties. Studies of Internet and community have found that information and communication technologies provide new opportunities for social interaction, but that they may also increase privatism by isolating people in their homes. This paper argues that while the Internet may encourage communication across great distances, it may also facilitate interactions near the home. Unlike traditional community networking studies, which focus on bridging the digital divide, this study focuses on bridging the divide between the electronic and parochial realms. Detailed, longitudinal social network surveys were completed with the residents of four contrasting neighborhoods over a period of three years. Three of the four neighborhoods were provided with a neighborhood email discussion list and a neighborhood website. Hierarchical linear modeling (HLM) was used to model over time the number of strong and weak ties, emailed, met in-person, and talked to on the telephone. The neighborhood email lists were also analyzed for content. The results suggest that with experience using the Internet, the size of local social networks and email communication with local networks increases. The addition of a neighborhood email list further increases the number of weak neighborhood ties, but does not increase communication multiplexity. However, neighborhood effects reduce the influence of everyday Internet use, as well as the experimental intervention, in communities that lack the context to support local tie formation.     

A comparison of email networks and off-line social networks: A study of a medium-sized bank

Recently there has been a surge in the availability of online data concerning the connections between people, and these online data are now widely used to map the social structure of communities. There has been little research, however, on how these new types of relational data correspond to classical measures of social networks. To fill this gap, we contrast the structure of an email network with the underlying friendship, communication, and advice seeking networks. Our study is an explorative case study of a bank, and our data contains emails among employees and a survey of the ego networks of the employees. Through calculating correlations with QAP standard errors and estimating exponential random graph (ERG) models, we find that although the email network is related to the survey-based social networks, email networks are also significantly different: while off-line social networks are strongly shaped by gender, tenure, and hierarchical boundaries, the role of these boundaries are much weaker in the email network.     

Chronic illness and social network bridging in later life

Chronic disease has profound impacts on the structural features of individuals’ interpersonal connections such as bridging — ties to people who are otherwise poorly connected to each other. Prior research has documented competing arguments regarding the benefits of network bridging, but less is known about how chronic illness influences bridging and its underlying mechanisms. Using data on 1555 older adults from the National Social Life, Health, and Aging Project (NSHAP), I find that older adults diagnosed with chronic illness tend to have lower bridging potential in their networks, particularly between kin and non-kin members. They also report more frequent interactions with close ties but fewer neighbors, friends, and colleagues in their networks, which mediates the association between chronic illness and social network bridging. These findings illuminate both direct and indirect pathways through which chronic illness affects network bridging and highlight the context-specific implications for social networks in later life.     

Mobility types,transnational ties and personal networks in four highly skilled immigrant communities in Seville (Spain)

In this study, we explore how different mobility patterns influence the composition and structure of the transnational social support networks and how personal networks allow us to elicit insightful data of mobile individuals. Ninety-five mobile individuals were selected from four distinct communities based in Seville (Spain), namely: Erasmus students, Flamenco artists, musicians from the symphonic orchestra and partners of European Commission researchers. Data were collected through an electronic survey sent by email with multiple name generators and a structured face-to-face interview utilizing a network visualization tool, VennMaker. Two distinct methods, namely qualitative case studies and cluster analysis were used to characterize mobility types. Findings reveal a heterogeneous foreign population, in which different forms of mobility are reflected in the personal networks of mobile individuals. Respondents who were settled in the city were more likely to have networks in which social support was mainly derived by hosts and people in the host location and with whom they communicated predominantly through face-to-face communication. Those who were in the host location for a study exchange, knowing that return to the county of origin is imminent were more likely to have networks linked to the home location. They relied heavily on strong transnational ties in the home country using social media to sustain their relationship. Respondents with an itinerant mobility profile, also had networks dominated by strong transnational ties, however, such ties had a higher degree of geographical spread due to previous international mobility. Participants who had a high number of hosts in the network but low connection between the ties were more likely to be linked to a specific subculture in the host society. The integration in the host location follows a different pattern to other settled individuals, mainly because their connection in the city tends to be community specific.     

Introduction: global knowledge and advocacy networks

As global and regional networks proliferate, one important aspect of their operations has been the exchange of knowledge, information and expertise. ‘Global knowledge networks’ have become important components of the global political economy. Within these networks key knowledge institutions and actors can be development agencies, foundations, think‐tanks, universities, consultancy firms as well as individual experts and academics. A primary mechanism for the spread of their knowledge has been through global and regional networks. The article evaluates first, concepts of networks, especially the epistemic community and transnational issue network frameworks; second, theories about international diffusion of ideas; and third, some of the literature on the links between ideas and politics. Control over knowledge and information is important to policy making. Additionally, the status and prestige associated with scholarly expertise and professional training is politically empowering for individual experts consulted or co‐opted into policy making. Yet, norms and values cannot be divorced from ‘scientific advice’ especially when knowledge gains greater impact through advocacy and alliance with societal forces.     

A New Model for Information Diffusion in Heterogeneous Social Networks

This paper discusses a new model for the diffusion of information through heterogeneous social networks. In earlier models, when information was given by one actor to another the transmitter did not retain the information. The new model is an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else. Consequently, the new model allows more actors to have information during the information diffusion process. The model provides predictions of diffusion times in a given network at the global, dyadic, and individual levels. This leads to straightforward generalizations of network measures, such as closeness centrality and betweenness centrality, for research problems that focus on the efficiency of information transfer in a network. We analyze in detail how information diffusion times and centrality measures depend on a series of network measures, such as degrees and bridges. One important finding is that predictions about the time actors need to spread information in the network differ considerably between the new and old models, while the predictions about the time needed to receive information hardly differ. Finally, some cautionary remarks are made about using the model in empirical research.     

Social fabric and fear of crime: Considering spatial location and time of day

Criminologists have long noted that social networks play a role in influencing residents' fear of crime, but findings vis a vis the exact nature of that role have been mixed. More social ties may be associated with less fear of crime through their role in collective action, trust, and emotional support, but also with more fear of crime because of their role in the diffusion of information on local crime patterns. In what follows, we suggest temporal and spatial distinctions in how social ties matter for fear of crime with respect to these different mechanisms. Analysis of data from a large scale egocentric network study in Southern California provides evidence for these claims.     

Who should we get? How employer reputation shapes network hiring in Dutch professional football

Despite a vast literature examining networks in labor markets, it remains unclear how employers differ in their use of networks during recruitment. This study examines network hiring among high and low reputation organizations in Dutch professional football. Within-employer within-transfer window fixed effects conditional logistic regression models demonstrate that networks increase the likelihood that low reputation employers hire workers, but no network effect was found among high reputation employers. Qualitative interviews with employees suggest that low reputation employers identify their search pool and gather hard-to-observe information about potential hires through networks, while high reputation employers do not rely on networks for their search pool and gather information through observing workers for prolonged periods of time     

Security branding and digital narrations. Security issues representation on Twitter

In the contemporary multicentric world, sovereign states have to manage carefully the construction of their image, defining their role and aspirations. With the re-definition of the state centric politics, stories become relevant: communication is a form of power, and networked forms of communication are becoming progressively a way to conquer the transnational public spheres. Through strategic narratives of foreign politics, states try to set up the ‘tales’ of international affairs and foreign strategies, to suggest a world vision, a causal interpretation, determining frames that affect transnational actors’ position in the international environment. Sovereign states develop these kind of frame using tools and theories referred to the commercial branding tradition to promote and support their own policies and identity. We decided to investigate how that process is made through information diffusion on digital platforms.

In this work, it has been analyzed the content presented through Twitter posts by the Foreign Ministries accounts of four different States dissimilar for geopolitical positioning and security concerns (USA; Israel; France; Sweden), for a period of three months (9/1/2015-11/30/2015); leading to the identification of different models and characteristic patterns of self-representation.

The thematic content analysis, based on the identification of macrocategories and micro-issues, has led to the identification of different models and characteristic patterns of self-representation, determined by domestic vicissitudes, and has shown some regularities, caused by the branding vocation of autobiographical online contents.     

Modeling the dynamism of HIV information diffusion in multiplex networks of homeless youth

Cascade and threshold models are widely used to predict information diffusion in social networks, yet their characterization of networks as static and monoplex limit their ability to accurately predict how information propagates in dynamic, multiplex social environments. Using data from a peer-led HIV prevention intervention for homeless youth, we determine whether manipulating the baseline social network by (1) adding ties observed at later time points, and (2) accounting for alternative relational contexts improves each model’s predictive accuracy. Results show that the addition of new ties improves the performance of both models, while substituting the context of interaction yields only minor improvements.     

SOCIAL HIERARCHIES: A LABORATORY STUDY ON PUNISHMENT PATTERNS ACROSS NETWORKS

We experimentally study punishment patterns across network structures, and their effect on cooperation. In a repeated public goods setting, subjects can only observe and punish their neighbors. Centralized structures (like the star network) outperform other incomplete networks and reach contribution levels like the ones observed in a complete network. Our results suggest that hierarchical network structures with a commonly observed player benefit more from sanctions not because central players punish more, but because they follow, and promote, different punishment patterns. While quasi-central players in other incomplete architectures (like the line network) retaliate, and get trapped in the vicious circle of antisocial punishment, central players in the star network do not punish back, increase their contributions when sanctioned by peripheral players, and sanction other participants in a prosocial manner. Our results illustrate recent field studies on the evolutionary prevalence of hierarchical networks. We document a network-based rationale for this positive effect in an identity-free, fully anonymous environment. (JEL C72, C91, C92, D90, H41)     

Transparency tested: The influence of message features on public perceptions of organizational transparency

The concept of transparency has been promoted within the public relations and business literature as both ethical and advantageous; however, the effectiveness of transparency is seldom empirically put to the test. In particular, the use of clarity, disclosure, and accuracy in organizational messages needs to be empirically examined. To this end, we conducted an online experiment using a 2 (high vs. low message transparency) x 2 (news story placed before or after an organizational statement) between-subjects design. Participants (n?=?357) perceived organizations as more transparent and credible when exposed to messages exhibiting greater levels of clarity, disclosure, and accuracy as opposed to messages that did not. Placement of an information anchor in the form of an objective news story before the organizational message increased the perceived organizational transparency when messages employed transparent design features and decreased the perceived organizational transparency when messages did not use these features. These results provide significant implications for practitioners attempting to convey organizational transparency at the tactical level through message features.     

Subject to Evaluation: How Parents Assess and Mobilize Information from Social Networks in School Choice

A rich literature examines how information spreads through social networks to influence life opportunities. However, receiving information does not guarantee its use in decision making. This article analyzes information evaluation as a fundamental component of social network mobilization. The case of school choice, where the value of information may be more uncertain, brings this evaluative dimension to the forefront. Interviews with 55 parents in Boston show how parents selecting schools assess their social network ties as information sources, privileging information from those they perceive to have affinity and authority. These evaluative criteria map onto disparate networks to engender unequal mobilization of this information. The findings illuminate mechanisms sustaining inequality in social network mobilization and reorient scholars to consider processes underlying information use alongside information diffusion to attain a more complete understanding of how network resources are mobilized in action.     

The adoption of external networking by American schools

Hypotheses from diffusion and resource dependence theory are applied to the explanation of participation in external networking (inter-networking) by schools. A national probability sample of 571 U.S. K-12 schools was used to test factors predicting schools’ use of external networks for instructional purposes. Early (vs late) adoption of computers did not predict later involvement in networking. Neither school spending nor rural region predicted network participation, except through the intervening variable of computer density. Thus, no matter how a school has acquired computers, once the base has been established it serves as an essential ingredient in taking the next step into external networking. The results were disappointing for diffusion theory and certainly point toward further investigation of this phenomenon. The findings also point to the importance of building a technological infrastructure in order to boost and leverage many of the instructional reform initiatives in education. where he has been since completing his Ph.D. at Stanford University in 1970. His primary specialty has been computing: developing computer-related methods in sociology as well as doing research on the social aspects of information technology. Shon Magnan is a Ph.D. candidate in sociology at the University of Minnesota and a research analyst at Questar Data Systems in Eagan Minnesota. This material is based on work supported by the National Science Foundation under grant number SED-9154511. Any opinions, findings, and conclusions expressed in this article do not necessarily reflect those of the National Science Foundation.     

Email subject lines and response rates to invitations to participate in a web survey and a face-to-face interview: the sound of silence

This paper investigates the relationship between blank and non-blank email subject lines on levels of response to a solicitation to participate in an interview, and on participation in a web survey. Email use has grown substantially in recent years, presenting significant opportunity to the empiricist seeking research respondents. However, response to emails may be low because growth in the sheer volume of messages that individuals receive per day has led to a sense of ‘email overload’, and faced with the challenge of personal email management, many recipients choose to ignore some messages, or do not read them all fully. Drawing on information gap theory, we expected that sending an invitation with a blank subject line would induce a sense of curiosity in recipients that would improve email response and willingness to participate in research studies. However, findings from research with two samples with different propensities to participate in research (academics and business owners) revealed that an email invitation with a blank subject line does not increase overall response rates to a web survey and a face-to-face interview over either an informative subject line or a provocative subject line, but that it does prompt a greater number of active refusals. Based on this finding, recommendations for researchers are outlined.     

Diffusion of innovations through social networks: Determinants and implications

Social scientists have long been interested in the diffusion of innovations—the process by which new ideas, behavior, and practices spread between persons, organizations, and even countries. While innovations can enter a community through various channels, ongoing spread of innovations through a community occurs through the medium of social networks—collections of interpersonal or digital relationships connecting actors to each other. Social networks are important for diffusion because relationships foster communication, trust, and flow of information. Diffusion outcomes are also shaped by the structural properties of social networks such as density, centrality, and strength of ties, as well as properties of the innovation and the actors involved in the process. The purpose of the article is twofold: (1) to take stock of the field and review ongoing debates on the role of social networks in the diffusion of innovations and (2) to summarize the sociological implications of the diffusion of innovations through social networks.     

Missing data in networks: exponential random graph (p1) models for networks with non-respondents

Survey studies of complete social networks often involve non-respondents, whereby certain people within the “boundary” of a network do not complete a sociometric questionnaire—either by their own choice or by the design of the study—yet are still nominated by other respondents as network partners. We develop exponential random graph (p¹) models for network data with non-respondents. We model respondents and non-respondents as two different types of nodes, distinguishing ties between respondents from ties that link respondents to non-respondents. Moreover, if we assume that the non-respondents are missing at random, we invoke homogeneity across certain network configurations to infer effects as applicable to the entire set of network actors. Using an example from a well-known network dataset, we show that treating a sizeable proportion of nodes as non-respondents may still result in estimates, and inferences about structural effects, consistent with those for the entire network.If, on the other hand, the principal research focus is on the respondent-only structure, with non-respondents clearly not missing at random, we incorporate the information about ties to non-respondents as exogenous. We illustrate this model with an example of a network within and between organizational departments. Because in this second class of models the number of non-respondents may be large, values of parameter estimates may not be directly comparable to those for models that exclude non-respondents. In the context of discussing recent technical developments in exponential random graph models, we present a heuristic method based on pseudo-likelihood estimation to infer whether certain structural effects may contribute substantially to the predictive capacity of a model, thereby enabling comparisons of important effects between models with differently sized node sets.     

Effects of temporal resolution adjustments on dynamic sexual contact models

Simulation and inferential modeling of sexual contact dynamics can be used to help predict the propagation of sexually transmitted infections (STI) such as HIV, by providing information on both cross-sectional network structure and how that structure changes over time. Researchers’ choices regarding the temporal resolution of such network models is often driven by the resolution of the data collected to support model fitting and evaluation. These inherited temporal resolutions can become problematic if they differ from the resolution of other processes to which the network must be related. In such cases, a model “correction” is necessary: specifically, we would like to have a systematic method for adjusting a fitted model to allow it to make predictions at a different timescale than the one on which it was initially based. Here, we introduce a basic set of desiderata for such adjustments, and assess three very simple approaches to timescale adjustments for models of sexual contact networks (SCNs), with focus on models parameterized within the separable temporal exponential family random graph model (STERGM) framework. We also examine the impact of time-scale changes on SCN characteristics themselves, and outline a set of desiderata for what an adjustment strategy may be expected to achieve. Our findings have implications both for timescale correction of dynamic network models, and for dynamic network data collection.     

Risk,trust and knowledge networks in farmers’ learning

This study reports on New Zealand dairy farmers’ access to and use of information as mediated through conditions of risk and trust within the context of their interpersonal social networks. We located participants’ reports of their information use within their perceived environments of trust and risk, following Giddens's [1990. The consequences of modernity. Polity Press, Stanford, CA] typology of trust and risk in pre-modernity and modernity. The research participants were constant users of interpersonal and print information from numerous sources, and monitored their incoming data in the light of strategic needs, reflecting their roles as both farming practitioners and business owners. Socio-spatial knowledge networks (SSKNs) combine individuals’ explanatory cognitive models of information acquisition and use with a micro-geographical analysis of their interpersonal networks. The participants showed characteristics of pre-modern, modern and even post-modern society in respect of their use of complex interactional forms, as well as a blending of individualistic and communitarian practices and concerns in their professional and personal lives.     

Marketization and Community in Post‐Soviet Russian Villages*

Abstract The introduction of new market institutions in former socialist countries has produced economic and social dislocations in people's lives. Researchers have focused on the impact of these changes on inequality and poverty, but have not given much attention to changes in community relationships. Panel data from surveys of Russian rural households (1995–1999) is used to examine post‐socialist changes in community involvement. The surveys show an overall increase in the number of redundant social network helping ties and a decrease in involvement in community‐wide social activities. Households with larger (non‐redundant) networks and more sales, however, have higher levels of community involvement than do their neighbors. Increases in the size of helping networks and increases in household sales from the first to second waves were associated with increases in level of community involvement. We discuss the implications of these findings for our general understanding of relationships between the marketplace and community.