Ecological Influences on the Formation of the Hiring Network in the Communication Job Market, 2015 to 2019

Network Ties ◽

Past Behavior ◽

This study investigates ecological factors that drive hiring decisions in the academic marketplace. Faculty hires between institutions are conceptualized as interorganizational network ties. Drawing on theoretical insights from network inertia and niche processes in organizational ecology, the current study builds an ecological framework to explain the formation mechanisms of the faculty hiring network among 81 U.S. institutions granting PhDs in communication. Consistent with the predictions of the ecological model of hiring decisions, the empirical results of exponential random graph models (ERGMs) revealed that past behavior (or the presence of previous ties), niche width (or the number of research specializations), and niche overlap (or the degree of shared research specializations) significantly constrained the likelihood of tie creation during the 2015 to 2019 period. These effects held true even when traditional explanations such as network self-organization and status-based hiring patterns were taken into account. Theoretical and practical implications are discussed.

Network Ecology and Adolescent Social Structure

American Sociological Review ◽

10.1177/0003122414554001 ◽

2014 ◽

Vol 79 (6) ◽

pp. 1088-1121 ◽

Cited By ~ 80

Author(s):

Daniel A. McFarland ◽

James Moody ◽

David Diehl ◽

Jeffrey A. Smith ◽

Reuben J. Thomas

Keyword(s):

Global Network ◽

Health Study ◽

Formation Mechanisms ◽

Network Clustering ◽

Network Structures ◽

Graph Models ◽

Organizational Environments ◽

Random Graph Models ◽

Adolescent societies—whether arising from weak, short-term classroom friendships or from close, long-term friendships—exhibit various levels of network clustering, segregation, and hierarchy. Some are rank-ordered caste systems and others are flat, cliquish worlds. Explaining the source of such structural variation remains a challenge, however, because global network features are generally treated as the agglomeration of micro-level tie-formation mechanisms, namely balance, homophily, and dominance. How do the same micro-mechanisms generate significant variation in global network structures? To answer this question we propose and test a network ecological theory that specifies the ways features of organizational environments moderate the expression of tie-formation processes, thereby generating variability in global network structures across settings. We develop this argument using longitudinal friendship data on schools (Add Health study) and classrooms (Classroom Engagement study), and by extending exponential random graph models to the study of multiple societies over time.

Duality beyond Dyads: Multiplex patterning of social ties and cultural meanings

10.31235/osf.io/xpf76 ◽

2020 ◽

Author(s):

Nikita Basov ◽

Julia Brennecke

Keyword(s):

Semantic Network ◽

Cultural Meanings ◽

Network Ties ◽

Shared Meanings ◽

The Social ◽

Interpersonal Ties ◽

Cultural Networks ◽

Cultural Structures

Purpose: The social and cultural duality perspective suggests dual ordering of interpersonal ties and cultural similarities. Studies to date primarily focus on cultural similarities in interpersonal dyads driven by principles such as homophily and contagion. We aim to extend these principles for socio-cultural networks and investigate potentially competing micro-principles that generate these networks, taking into account not only direct dyadic overlap between interpersonal ties and cultural structures, but also the indirect interplay between the social and the cultural. Methodology: The empirical analysis utilizes social and semantic network data gathered through ethnographic studies of five creative organizations around Europe. We apply exponential random graph models (ERGMs) for multiplex networks to model the simultaneous operation of several generative principles of socio-cultural structuring yielding multiplex dyads and triads that combine interpersonal ties with meaning sharing links. Findings: The results suggest that in addition to the direct overlap of shared meanings and interpersonal ties, socio-cultural structure formation is also affected by extra-dyadic links. Namely, expressive interpersonal ties with common third persons condition meaning sharing between individuals, while meaning sharing with common alters leads to interpersonal collaborations. Beyond dyads, the dual ordering of the social and the cultural thus operates as asymmetrical with regard to different types of interpersonal ties. Research implications: The paper shows that in addition to direct dyadic overlap, network ties with third parties play an important role for the co-constitution of the social and the cultural. Moreover, we highlight that the concept of network multiplexity can be extended beyond its application social networks to investigate competing micro-principles guiding the interplay of social and cultural structures.

A Bayesian networks approach to infer social changes in burials in northeastern Taiwan during the European colonization period

10.31235/osf.io/3vfea ◽

2021 ◽

Author(s):

Li-Ying Wang ◽

Ben Marwick

Keyword(s):

Network Analysis ◽

Iron Age ◽

Network Formation ◽

Network Ties ◽

Archaeological Data ◽

Robust Model ◽

European Colonization ◽

Colonization Period

Burials provide valuable information to study social structures based on the assumption that burials and associated grave goods can represent social roles and relations in a society. To study social relationships, network analysis has been increasingly applied to archaeological data to infer interactions and relationships between entities. Statistical approaches to network analysis, such as exponential random graph models (ERGMs), provide a way to test hypotheses about dynamic processes of network formation. However, computational difficulties and sensitivity to uncertainties limit the application of ERGMs. In this paper, we introduce a Bayesian framework on ERGMs that enables an efficient computational process, effective quantification of uncertainty, and robust model evaluation of network properties. We tested a hypothesis of social change relative to the arrival of Europeans by studying burial data from Kiwulan, an Iron Age site in northeastern Taiwan. The results indicate a transition among the burials from network ties based on ritual objects to wealth objects, and a more centralized structure with increased social differentiation after the European presence was established in the 17th century. Our case study demonstrates the effectiveness of Bayesian network analysis for archaeological data, and expands the use of burials in understanding the impacts of colonial presence on Indigenous groups in a pericolonial context.

Can policy forums overcome echo chamber effects by enabling policy learning? Evidence from the Irish climate change policy network

Journal of Public Policy ◽

10.1017/s0143814x18000314 ◽

2018 ◽

Vol 40 (2) ◽

pp. 194-211 ◽

Cited By ~ 7

Author(s):

Paul M. Wagner ◽

Tuomas Ylä-Anttila

Keyword(s):

Climate Change ◽

Climate Change Policy ◽

Policy Advice ◽

Policy Learning ◽

Policy Network ◽

Network Ties ◽

Change Policy ◽

Echo Chambers

AbstractResearch has repeatedly shown that individuals and organisations tend to obtain information from others whose beliefs are similar to their own, forming “echo chambers” with their network ties. Echo chambers are potentially harmful for evidence-based policymaking as they can hinder policy learning and consensus building. Policy forums could help alleviate the effects of echo chambers if organisations with different views were to participate and to use the opportunities that forums provide to learn from those outside their networks. Applying exponential random graph models on survey data of the Irish climate change policy network, we find that policy actors do indeed tend to obtain policy advice from those whose beliefs are similar to their own. We also find that actors tend not to obtain policy advice from the those that they encounter at policy forums, suggesting forums are not enabling policy learning.

From network ties to network structures: Exponential Random Graph Models of interorganizational relations

Quality & Quantity ◽

10.1007/s11135-011-9619-6 ◽

2011 ◽

Vol 47 (3) ◽

pp. 1665-1685 ◽

Cited By ~ 16

Author(s):

Francesca Pallotti ◽

Alessandro Lomi ◽

Daniele Mascia

Keyword(s):

Random Graph ◽

Interorganizational Relations ◽

Network Structures ◽

Network Ties ◽

Graph Models ◽

Random Graph Models ◽

Building Consensus: Idea Brokerage in Teacher Policy Networks

American Educational Research Journal ◽

10.3102/0002831219872738 ◽

2019 ◽

Vol 57 (2) ◽

pp. 872-905

Author(s):

Sarah Galey-Horn ◽

Sarah Reckhow ◽

Joseph J. Ferrare ◽

Lorien Jasny

Keyword(s):

Teacher Effectiveness ◽

Policy Networks ◽

Policy Preferences ◽

Network Ties ◽

Graph Models ◽

Congressional Hearings ◽

Political Actors ◽

Random Graph Models ◽

We show how policy makers converged to support similar reforms on a major educational issue: teacher effectiveness. Our study demonstrates the importance of idea brokers—actors that facilitate connections between preferences in policy networks and promote consensus around new policy ideas. Our study is based on analysis of testimony from 200 Congressional hearings from 2001 to 2015. We use discourse network analysis to examine network ties based on policy preferences expressed in hearings. We visualize policy networks, identify brokers, and estimate exponential random graph models to examine policy changes between the Bush and Obama administrations. We show how idea brokerage is associated with a convergence of policy preferences around teacher effectiveness among a coalition of political actors.

Political Interaction Beyond Party Lines: Communication Ties and Party Polarization in Parliamentary Twitter Networks

Social Science Computer Review ◽

10.1177/0894439320987569 ◽

2021 ◽

pp. 089443932098756

Author(s):

Marc Esteve Del Valle ◽

Marcel Broersma ◽

Arnout Ponsioen

Keyword(s):

Social Media ◽

Political Parties ◽

Geographical Area ◽

Political Polarization ◽

Party Polarization ◽

Political Networks ◽

Use Of Social Media ◽

High Degree

A growing body of research has examined the uptake of social media by politicians, the formation of communication ties in online political networks, and the interplay between social media and political polarization. However, few studies have analyzed how social media are affecting communication in parliamentary networks. This is especially relevant in highly fragmented political systems in which collaboration between political parties is crucial to win support in parliament. Does MPs’ use of social media foster communications among parliamentarians who think differently, or does it result in like-minded clusters polarized along party lines, confining MPs to those who think alike? This study analyzes the formation of communication ties and the degree of homophily in the Dutch MPs’ @mention Twitter network. We employed exponential random graph models on a 1-year sample of all tweets in which Dutch MPs mentioned each other ( N = 7,356) to discover the network parameters (reciprocity, popularity, and brokerage) and individual attributes (seniority, participation in the parliamentary commissions, age, gender, and geographical area) that facilitate communication ties among parliamentarians. Also, we measured party polarization by calculating the external–internal index of the mentions. Dutch MPs’ communication ties arise from network dynamics (reciprocity, brokerage, and popularity) and from MPs’ participation in the parliamentary commissions, age, gender, and geographical area. Furthermore, there is a high degree of cross-party interactions in the Dutch MPs’ mentions Twitter network. Our results refute the existence of “echo chambers” in the Dutch MPs’ mentions Twitter network and support the hypothesis that social media can open up spaces for discussion among political parties. This is particularly important in fragmented consensus democracies where negotiation and coordination between parties to form coalitions is key.

Exponential random graph models for little networks

Social Networks ◽

10.1016/j.socnet.2020.07.005 ◽

2021 ◽

Vol 64 ◽

pp. 225-238

Author(s):

George G. Vega Yon ◽

Andrew Slaughter ◽

Kayla de la Haye

Keyword(s):

Random Graph ◽

Graph Models ◽

Random Graph Models ◽

Investigation of Rater Effects Using Social Network Analysis and Exponential Random Graph Models

Educational and Psychological Measurement ◽

10.1177/0013164416689696 ◽

2017 ◽

Vol 78 (3) ◽

pp. 430-459 ◽

Cited By ~ 3

Author(s):

Iasonas Lamprianou

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Graph Models ◽

High Stakes ◽

Rating Data ◽

New Approach ◽

Rater Severity

It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as “markers” or “judges”) demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new methods to analyze rating data. We used simulated and empirical data from two high-stakes language assessments, to propose a new approach, based on social network analysis and exponential graph models, to evaluate the readiness of a group of raters for operational rating. The results of this innovative approach are compared with the results of a Rasch analysis, which is a well-established approach for the analysis of such data. We also demonstrate how the new approach can be practically used to investigate important research questions such as whether rater severity is stable across rating tasks. The merits of the new approach, and the consequences for practice are discussed.

Why Legislative Networks? Analyzing Legislative Network Formation

Political Science Research and Methods ◽

10.1017/psrm.2017.37 ◽

2017 ◽

Vol 7 (3) ◽

pp. 505-522 ◽

Cited By ~ 4

Author(s):

Stefan Wojcik

Keyword(s):

Political Parties ◽

Network Formation ◽

Contemporary Literature ◽

Party Organization ◽

Graph Models ◽

Personal Traits ◽

Random Graph Models ◽

The Social

Are the social networks of legislators affected more by their political parties or their personal traits? How does the party organization influence the tendency of members to work collectively on a day-to-day basis? In this paper, I explore the determinants of the relationships of legislators in the Brazilian Chamber of Deputies. I use exponential random graph models to evaluate the relative influence of personal traits versus party influence in generating legislator relationships. Despite a focus on personalism in Brazil, the analysis reveals that the effects of political parties on tie formation are roughly equal to the effects of personal traits, suggesting that networks may make political parties much more cohesive than contemporary literature would lead us to believe.