<abstract>
<title style='display:none'>Abstract</title>
Network evolution is an important problem for social scientists, management consultants, and social network scholars. Unfortunately, few empirical data sets exist that have sufficient data to fully explore evolution dynamics. Increasingly, more and more online data sets are used in lieu of offline, face-to-face data. The veracities of these findings are questionable, however, because there are few studies exploring the similarity of online-offline dynamics. The IkeNet project investigated online and offline network evolution. Empirical data was collected on a group of 22 mid-career military officers going through a one-year graduate program. Data collection included email communication collected from the Exchange server, as well as self-reported friendship, and time spent together, over a course of 20 weeks. Numerous attribute data on the individual actors was collected from their military personnel files. The data allows network scholars to conduct research into the dynamics of network evolution and allows educators a real-world example data set for use in classroom instruction.
</abstract>

Ike Net: Email and Friendship Evolution

<abstract>
<title style='display:none'>Abstract</title>
This paper is the text prepared for the keynote address of the EUSN 2017 conference in Mainz, Germany. A short presentation of concepts reflects in part the foundations of neo-structural sociology (NSS) and its use of social and organisational network analyses, combined with other methodologies, to better understand the roles of structure and culture in individual and collective agency. The presentation shows how NSS accounts for institutional change by focusing on the importance of combined relational infrastructures and rhetorics. Specific characteristics of institutional entrepreneurs who punch above their weight in institutionalization processes are introduced for that purpose, particularly the importance of multi-status oligarchs, status heterogeneity, high-status inconsistencies, collegial oligarchies, conflicts of interests and rhetorics of relative/false sacrifice. Two empirical examples illustrate this approach. The first case focuses on a network study of the Commercial Court of Paris, a 450-year-old judicial institution. The second case focuses on a network study of a field-configuring event (the so-called Venice Forum) lobbying for the emergence of a new European jurisdiction, the Unified Patent Court, and its attempt to create a common intellectual property regime for the continent. For sociologists, both examples involve “studying up”: they are cases of public/private joint regulation of markets bringing together these ingredients of institutionalization. The conclusion suggests future lines of research that NSS opens for the study of institutionalization, in particular using the dynamics of multi-level networks. One of the main issues raised by this approach is its contribution to the study of democratic deficits in a period of intense institutional change in Europe.
</abstract>

Networks and Institutionalization: A Neo-structural Approach

<abstract>
<title style='display:none'>Abstract</title>
Network methods have been applied to obesity to map connections between obesity-related genes, model biological feedback mechanisms and potential interventions, and to understand the spread of obesity through social networks. However, network methods have not been applied to understanding the obesogenic environment. Here, we created a network of 32 features of communities hypothesized to be related to obesity. Data from an existing study of determinants of obesity among 1,288 communities in Pennsylvania were used. Spearman correlation coefficients were used to describe the bivariate association between each pair of features. These correlations were used to create a network in which the nodes are community features and weighted edges are the strength of the correlations among those nodes. Modules of clustered features were identified using the walktrap method. This network was plotted, and then examined separately for communities stratified by quartiles of child obesity prevalence. We also examined the relationship between measures of network centrality and child obesity prevalence. The overall structure of the network suggests that environmental features geographically co-occur, and features of the environment that were more highly correlated with body mass index were more central to the network. Three clusters were identified: a crime-related cluster, a food-environment and land use-related cluster, and a physical activity-related cluster. The structure of connections between features of the environment differed between communities with the highest and lowest burden of childhood obesity, and a higher degree of average correlation was observed in the heaviest communities. Network methods may help to explicate the concept of the obesogenic environment, and ultimately to illuminate features of the environment that may serve as levers of community-level intervention.
</abstract>

A network approach to understanding obesogenic environments for children in Pennsylvania

<abstract>
<title style='display:none'>Abstract</title>
The development of the “public sphere” and the Enlightenment are closely related to the networks of publishers involved in print culture. In Britain, a key question is whether diversity (in terms of nationality) in publishing increased over time. In this paper, we use large-scale library catalog data and a class of models known as Exponential Random Graph Models (ERGMs) to investigate the extent to which an 18th-century network of publishers in London was homophilous with respect to nationality, and specifically investigate whether those with close publishing connections to Scotland formed a separate group or if they were simply integrated into the London book market. As there is little external information on the majority of publishers, we generate node and edge attributes from the catalog data itself. The results suggest that social processes were deeply involved in the decisions behind copublishing and collaborations and that there is indeed a significant positive effect on tie formation if both nodes are “Scottish” publishers, though this lessens over the century. We find that other important factors in tie formation are edgewise shared partners and similarity in patterns of genres published.
</abstract>

Networks of Influence in Scottish Enlightenment Publishing

<abstract><title style='display:none'>Abstract</title>The book “Conducting Personal Network Research” is a conceptual and methodological introduction to the structural study of personal networks. It is part of a series of recent monographs that have begun to systematize the knowledge generated in this area in recent decades (Crossley et al., 2015; McCarty et al., 2019; Perry et al., 2018). In this case, the authors have dedicated a large part of their career to the empirical investigation of the interpersonal relationships, interaction contexts, and social integration processes of immigrants, along with other groups in vulnerable situations. With this publication, all this experience is now reflected in a clear and comprehensive introductory text. This book explains how to integrate relational data collection and analysis with survey research. It systematically presents the strategies to estimate the size of personal networks. Finally, it describes how to fit statistical analysis to relational data, including regression models, multi-level models, and longitudinal models.</abstract>

Commentary: How to do personal network surveys: from name generators to statistical modeling

<abstract>
<title style='display:none'>Abstract</title>
Departing from Roberto Michels’s classic analysis of oligarchy, we provide a structural analysis of the concept based on social network analysis. We define oligarchy as a social network that exhibits three structural properties: tight interconnections among a small group of prominent actors who form an “inner circle”; the organization of other actors in the network through the intermediation of this inner circle; and weak direct connections among the actors outside the inner circle. We treat oligarchy as a global property of social networks and offer an approach for measuring the oligarchical tendencies of any social network. Our main contribution is to operationalize this idea using a “rich club” approach. We demonstrate the efficacy of this approach by analyzing and comparing several urban networks: Sao Paulo urban infrastructure networks and Los Angeles and Chicago transportation policy networks.
</abstract>

Who Says Networks, Says Oligarchy? Oligarchies as “Rich Club” Networks

<abstract>
<title style='display:none'>Abstract</title>
Despite a rapid increase in research on the underpinnings of misinformation susceptibility, scholars still disagree about the relative impacts of social context and individual cognitive factors. We argue that cognitive reflection and identity-based network homogeneity may have unique influences on different types of misinformation. Specifically, identity-based network homogeneity predicts bias that is related to any type of identity-based information (i.e., political rumors), and cognitive reflection is more tailored toward truth discernment (i.e., fake news headlines). We conducted our study using an online sample (N = 214) split evenly between Democrats and Republicans and collected data on personal network composition, cognitive reflection, as well as susceptibility, sentiments, and sharing behavior in relation to political rumors and misinformation, respectively. Results demonstrate that where network homogeneity predicts belief and sharing in both political rumors and fake news headlines, cognitive reflection only predicts belief and sharing of fake news headlines. Social vs. cognitive factors for predicting different types of misinformation are discussed.
</abstract>

Personal Network Composition and Cognitive Reflection Predict Susceptibility to Different Types of Misinformation

<abstract>
<title style='display:none'>Abstract</title>
Problem-solving effectiveness is key to organizational performance. To solve problems, gathering information from colleagues is critical, and positioning brokerage in communication networks is beneficial. The communication network for problem-solving is formed depending on the nature of the problem. Thus, the problem-solving network is the relational event network, and the connection of the problem-solving network dynamically changes over time depending on the problem basis. This study investigates the dynamics of brokerage in a problem-solving network and its impact on productivity in a company that provides technical support and troubleshooting for the IT system that its corporate customers use. By exploiting high-frequency data on face-to-face communication among employees collected by wearable sensors, we established the following results. First, the communication partners of each employee change weekly, which is a reasonable time to solve problems in the company. Second, with the change in the communication network, employees who position brokerage also change on a weekly basis. Third, while brokerage in a week has a positive impact on employee performance during the week, it has no impact on employee performance in the following week.
</abstract>

The Impact of Brokerage in a Communication Network on Productivity: Evidence from Sensor Data

<abstract>
<title style='display:none'>Abstract</title>
Fractals describe structural details at arbitrarily small scales, but are mathematically not necessarily complex, presenting a pragmatic way of describing nature. They are also common in social settings, including the organizational space. However, attention has been devoted to temporal fractal patterns in heterarchical or networked organizations. This article leverages data on face-to-face interactions collected by the SocioPatterns collaboration in a public sector organization to investigate temporal fractal patterns in interaction networks and three types of processes have been identified in this. White noise exhibits no correlation in time with rapid, chaotic changes. Brown noise entails a diffusion process with stable, structural patterns, but no quick adaptation. Pink noise exhibits an equilibrium between the two, producing dynamics that maintain stable patterns of interactions, remaining flexible to regulate interaction. The interaction network is described with metrics of social network analysis, and analyzed with detrended fluctuation analysis (DFA) to detect temporal fractal patterns within the three largest departments as well as the whole organization. Results indicate high levels of pink noise with traces of white noise in the departments as well as pink noise with traces of brown noise on the organizational level. While previous research found pink noise processes in self-organizing networks, this article extends them to structured intraorganizational networks. The low levels of brown noise question the influence of rigid organizational structures and processes on the temporal structure of interaction. Hence, the fractal temporal structure of the interactions themselves is a factor that contributes to the stability of interactions between individuals over time.
</abstract>

Fractals Beyond Hierarchy—Analyzing the Temporal Patterns of Contact Networks in a French Public Sector Organization

<abstract>
<title style='display:none'>Abstract</title>
Most recent academic studies of homophily—the tendency of people to interact with similar others—lean to a sociological critique of digital technologies, rather than revealing fundamentally positive outcomes. A few solid philosophical endeavors have emerged from the fields of philosophy of technology and enactive ethics. This article adopts a sociological perspective to argue that digital social networks can serve as an ethical infrastructure for facilitating effective communication. However, they also face the challenge of organizing the myriad of individual voices present within them, so that the necessary moral conditions to mitigate homophily can be established. From this viewpoint, it is suggested homophily should be viewed not as an individual’s right to expression but as a cultivated echo-moral cultured landscape. Homophily is not an input but an outcome. Homophily does not happen without evaluating reception. A voice without assessment lacks the ethical dimension. By applying the theory of the social construction of reality (<xref ref-type="bibr" rid="j_connections-2019.037_ref_003">Berger &amp; Luckmann, 2008</xref>), homophily can be conceived as the contribution of <italic>significant others</italic>. Most importantly, effective communication can be attained when new secondary institutions organize the input of <italic>significant others</italic> into a meaningful <italic>generalized other</italic> (<xref ref-type="bibr" rid="j_connections-2019.037_ref_021">Mead, 2015</xref>). As a result, I propose that digital technologies allow for ameliorating the moral character of the individual by shifting how one looks at communication: from an individual’s right to a voice into an ordered culture of <italic>voices</italic>, from preserving rights to serving rightly. This perspective could illuminate policymakers to establish right processes to avoid homophily and help individuals and organizations achieve effective means of communication and deliberation.
</abstract>

Homophily vs the Generalized Other

<abstract>
<title style='display:none'>Abstract</title>
This paper examines the dissemination of Cartesianism in the 17th century by studying the networks of authors in the field of natural philosophy. Key figures who spread knowledge and innovated the field are identified and contextualized. Furthermore, the network analysis shows how different ways of thinking coexisted within the social networks of early modern natural philosophers. To achieve this methodologically, originally bipartite networks were projected into author-to-author networks that were divided into time slices. Measurements of centrality and assortativity were used to determine prominence and diversity, which were complemented and refined with close reading. The findings reveal not only cliques of geographically connected authors, but also an overall highly connected field. Additionally, assortativity indicates a moderate tendency toward homophily in the authors’ connections to others within the same philosophical tradition. The study furthermore identifies that central authors were predominantly eclectic or Cartesian, suggesting that Cartesianism was driven by such individuals in structurally well-connected positions.
</abstract>

Intelligencers, Cliques, and Stars in the Spread of 17th -Century Cartesianism

<abstract>
<title style='display:none'>Abstract</title>
This study analyses the frame resonance in the Twitter debate of Gustavo Petro and, especially, of Francia Márquez’s rhetoric during the presidential elections campaign of 2022. I specifically study the potential resonance of the notion of Otherness in tweets attributed to women and to men. I apply several methodological protocols including network analysis and topic modeling. The results are positive on the frame resonance of the campaign and Francia Márquez rhetoric in both groups, showing ideological-political engagement from a semantic view more than a gendered connection. However, semantic relatedness to the particular framing studied here appears to be stronger in women than in men. Addressing Twitter attributes such as mentions and hashtags is similar in both groups.
</abstract>

Framing Otherness on Twitter: gender, elections and networks

<abstract>
<title style='display:none'>Abstract</title>
This <italic>techniques</italic> guide provides a brief answer to the question: How to choose a dichotomization threshold? We propose a two step approach to selecting a dichotomization threshold. We illustrate the approaches using two datasets and provide instructions on how to perform these approaches in R and UCINET.
</abstract>

Techniques: Dichotomizing a Network

<abstract><title style='display:none'>Abstract</title>Coronavirus disease of 2019 (COVID-19)’s devastating effects on the physical and mental health of the public are unlike previous medical crises, in part because of people’s collective access to communication technologies. Unfortunately, a clear understanding of the diffusion of health information on social media is lacking, which has a potentially negative impact on the effectiveness of emergency communication. This study applied social network analysis approaches to examine patterns of #COVID19 information flow on Twitter. A total of 1,404,496 publicly available tweets from 946,940 U.S. users were retrieved and analyzed. Particular attention was paid to the structures of retweet and mention networks and identification of influential users: information sources, disseminators, and brokers. Overall, COVID-19 information was not transmitted efficiently. Findings pointed to the importance of fostering connections between clusters to promote the diffusion in both networks. Lots of localized clusters limited the spread of timely information, causing difficulty in establishing any momentum in shaping urgent public actions. Rather than health and communication professionals, there was dominant involvement of non-professional users responsible for major COVID-19 information generation and dissemination, suggesting a lack of credibility and accuracy in the information. Inadequate influence of health officials and government agencies in brokering information contributed to concerns about the spread of dis/misinformation to the public. Significant differences in the type of influential users existed across roles and across networks. Conceptual and practical implications for emergency communication strategies are discussed.</abstract>

COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers

<abstract>
<title style='display:none'>Abstract</title>
The graphic representation of relational data is one of the central elements of social network analysis. In this paper, the author describe the use of visualization in interview-based data collection procedures designed to obtain personal networks information, exploring four main contributions. First, the author shows a procedure by which the visualization is integrated with traditional name generators to facilitate obtaining information and reducing the burden of the interview process. Second, the author describes the reactions and qualitative interpretation of the interviewees when they are presented with an analytical visualization of their personal network. The most frequent strategies consist in identifying the key individuals, dividing the personal network in groups and classifying alters in concentric circles of relative importance. Next, the author explores how the visualization of groups in personal networks facilitates the enumeration of the communities in which individuals participate. This allows the author to reflect on the role of social circles in determining the structure of personal networks. Finally, the author compares the graphic representation obtained through spontaneous, hand-drawn sociograms with the analytical visualizations elicited through software tools. This allows the author to demonstrate that analytical procedures reveal aspects of the structure of personal networks that respondents are not aware of, as well as the advantages and disadvantages of using both modes of data collection. For this, the author presents findings from a study of highly skilled migrants living in Spain (<italic>n</italic> = 95) through which the author illustrates the challenges, in terms of data reliability, validity and burden on both the researcher and the participants.
</abstract>

What the eye does not see: visualizations strategies for the data collection of personal networks

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Connections

Connections publishes original empirical, theoretical, and methodological articles, as well as critical reviews dealing with applications of social network analysis. From...

MNiSW

Connections publishes original empirical, theoretical, and methodological articles, as well as critical reviews dealing with...

Connections

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