scholarly journals Multilevel social spaces: The network dynamics of organizational fields

2017 ◽  
Vol 5 (2) ◽  
pp. 187-212 ◽  
Author(s):  
JAMES HOLLWAY ◽  
ALESSANDRO LOMI ◽  
FRANCESCA PALLOTTI ◽  
CHRISTOPH STADTFELD
Keyword(s):  
Social Network ◽  
Goodness Of Fit ◽  
Social Space ◽  
Network Dynamics ◽  
Multilevel System ◽  
Organizational Field ◽  
Organizational Fields ◽  
Fit Statistics ◽  
Network Methods ◽  
Over Time

AbstractIn this paper, we seek to advance an updated concept of social space that integrates the multilayer and dynamic statistical network methods currently at the disposal of social network researchers. We demonstrate the analytic value of the new concept of social space that we propose with the help of an illustrative analysis of an organizational field involving organizations' external and internal decisions that congeal into a multilevel system of action that shapes the space of possibilities for other participants in the field. Through these internal and external decisions, organizations seek certain positions in their social space while simultaneously modifying that social space over time. We conclude by arguing that network researchers' choices of goodness-of-fit statistics should reflect a consideration about the dimensions of social space of most interest to the nodes involved.

scholarly journals Forecasting Origin-Destination-Age-Sex Migration Flow Tables with Multiplicative Components

2020 ◽  
pp. 217-242
Author(s):  
James Raymer ◽  
Xujing Bai ◽  
Peter W. F. Smith
Keyword(s):  
Goodness Of Fit ◽  
Time Series Models ◽  
Age Group ◽  
Interstate Migration ◽  
Migration Flow ◽  
Migration Patterns ◽  
Fit Statistics ◽  
Best Fitting ◽  
Time Periods ◽  
Over Time

Abstract In this chapter, we show how multiplicative components that capture the underlying structures of migration flow tables can be used to inform forecasts of interstate migration in Australia. For our illustration, we decompose 5-year census migration flow tables by state or territory of origin, state or territory of destination, 5-year age group and sex for seven census time periods from 1981–1986 to 2011–2016. The components are described over time and then fitted with time series models to produce holdout sample forecasts of interstate migration with measures of uncertainty. Goodness-of-fit statistics and calibration are then used to identify the best fitting models. The results of this research provide (i) insights into the different migration patterns of an important aspect of subnational population growth in Australia and (ii) potential inputs for standard or multiregional cohort component projection models.

scholarly journals Contextual Factors That Enable and Restrain Social Network Formation of Dutch Erasmus+ Students

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yentl Schoe ◽  
Christof Van Mol ◽  
Michael Buynsters
Keyword(s):  
Social Network ◽  
Social Space ◽  
Network Formation ◽  
Blind Spot ◽  
International Exchange ◽  
Interaction Patterns ◽  
Exchange Students ◽  
Studying Abroad ◽  
Social Network Formation ◽  
Over Time

When studying abroad, international exchange students generally establish a new social network abroad. However, how international exchange students develop their social networks over time remains a blind spot in the academic literature. In this paper, we therefore analyze the initial formation and development of such networks among six Dutch Erasmus+ students. Starting from homophily theory, we particularly focus on the factors that enable and restrain initial social network formation and interaction patterns. Methodologically, we rely on a longitudinal qualitative approach, whereby we repeatedly interviewed these six students over time. Our findings reveal the importance of three main contexts in the initial social network formation of Erasmus+ students, namely the pre-mobility phase, the living place, and the social space. These findings provide insights for practitioners on which contexts to focus on when developing strategies to foster the integration of international exchange students at host institutions.

The Lead Igniter: A Longitudinal Examination of Influence and Energy Through Networks, Efficacy, and Climate

2018 ◽  
Vol 55 (3) ◽  
pp. 363-403 ◽  
Author(s):  
Yi-Hwa Liou ◽  
Alan J. Daly
Keyword(s):  
Social Network ◽  
Interpersonal Relationships ◽  
Social Space ◽  
Social Aspect ◽  
Complex Nature ◽  
Educational Systems ◽  
Work Related ◽  
The Social ◽  
Work Level ◽  
Over Time

Purpose: The social aspect of leadership is often overlooked in the educational reform. This study aims to address the dearth of work in the social space around leadership and examines two different types of relational ties between leaders that capture the affective and work-related aspects of interpersonal relationships. Research Method: This study takes place in one large urban school district serving a highly diverse student population and investigates a multiplex relation—energy and work-related influence—from a longitudinal dataset to better understand the complex nature of social ties. Descriptive statistics, multilevel social network modeling, and network sociograms are used to understand the characteristics of this over-time multiplex relationship among central office and site leaders. Findings: Drawing on social network theory, efficacy, and climate, findings suggest that gender, work level, experience, efficacy, and climate are associated with leaders engaging in this multiplex relationship over time. Conclusion and Implications: Investigating the intersection of both affective and instrumental relationships provides a nuanced and more reality-based picture about a complex set of leadership ties and perceptions as they go about improving educational systems.

Developing a sustainable Digital Health Innovation Ecosystem in a rural and resource-poor region: A monitored networking approach (Preprint)

2020 ◽  
Author(s):  
Arunangsu Chatterjee ◽  
Sebastian Stevens ◽  
Sheena Asthana ◽  
Ray B Jones
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Data Collection ◽  
Digital Health ◽  
Resource Poor Setting ◽  
Quadruple Helix ◽  
Innovation Ecosystem ◽  
Resource Poor ◽  
Quadruple Helix Model ◽  
Over Time

BACKGROUND Digital health (DH) innovation ecosystems (IE) are key to the development of new e-health products and services. Within an IE, third parties can help promote innovation by acting as knowledge brokers and the conduits for developing inter-organisational and interpersonal relations, particularly for smaller organisations. Kolehmainen’s quadruple helix model suggests who the critical IE actors are, and their roles. Within an affluent and largely urban setting, such ecosystems evolve and thrive organically with minimal intervention due to favourable economic and geographical conditions. Facilitating and sustaining a thriving DH IE within a resource-poor setting can be far more challenging even though far more important for such peripheral economics and the health and well-being of those communities. OBJECTIVE Taking a rural and remote region in the UK, as an instance of an IE in a peripheral economy, we adapt the quadruple helix model of innovation, apply a monitored social networking approach using McKinsey’s Three Horizons of growth to explore: • What patterns of connectivity between stakeholders develop within an emerging digital health IE? • How do networks develop over time in the DH IE? • In what ways could such networks be nurtured in order to build the capacity, capability and sustainability of the DH IE? METHODS Using an exploratory single case study design for a developing digital health IE, this study adopts a longitudinal social network analysis approach, enabling the authors to observe the development of the innovation ecosystem over time and evaluate the impact of targeted networking interventions on connectivity between stakeholders. Data collection was by an online survey and by a novel method, connection cards. RESULTS Self-reported connections between IE organisations increased between the two waves of data collection, with Small and Medium-sized Enterprises (SMEs) and academic institutions the most connected stakeholder groups. Patients involvement improved over time but still remains rather peripheral to the DH IE network. Connection cards as a monitoring tool worked really well during large events but required significant administrative overheads. Monitored networking information categorised using McKinsey’s Three Horizons proved to be an effective way to organise networking interventions ensuring sustained engagement. CONCLUSIONS The study reinforces the difficulty of developing and sustaining a DH IE in a resource-poor setting. It demonstrates the effective monitored networking approach supported by Social Network Analysis allows to map the networks and provide valuable information to plan future networking interventions (e.g. involving patients or service users). McKinsey’s Three Horizons of growth-based categorisation of the networking assets help ensure continued engagement in the DH IE contributing towards its long-term sustainability. Collecting ongoing data using survey or connection card method will become more labour intensive and ubiquitous ethically driven data collection methods can be used in future to make the process more agile and responsive.

scholarly journals Using Ultrasound and Inflammation to Improve Prediction of Ischemic Stroke: A Secondary Analysis of the Multi-Ethnic Study of Atherosclerosis

2021 ◽  
pp. 37-43
Author(s):  
Hediyeh Baradaran ◽  
Alen Delic ◽  
Ka-Ho Wong ◽  
Nazanin Sheibani ◽  
Matthew Alexander ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Goodness Of Fit ◽  
Primary Outcome ◽  
Stroke Risk ◽  
Secondary Analysis ◽  
Predictor Variables ◽  
Baseline Model ◽  
Fit Statistics ◽  
Ischemic Stroke Risk

Introduction: Current ischemic stroke risk prediction is primarily based on clinical factors, rather than imaging or laboratory markers. We examined the relationship between baseline ultrasound and inflammation measurements and subsequent primary ischemic stroke risk. Methods: In this secondary analysis of the Multi-Ethnic Study of Atherosclerosis (MESA), the primary outcome is the incident ischemic stroke during follow-up. The predictor variables are 9 carotid ultrasound-derived measurements and 6 serum inflammation measurements from the baseline study visit. We fit Cox regression models to the outcome of ischemic stroke. The baseline model included patient age, hypertension, diabetes, total cholesterol, smoking, and systolic blood pressure. Goodness-of-fit statistics were assessed to compare the baseline model to a model with ultrasound and inflammation predictor variables that remained significant when added to the baseline model. Results: We included 5,918 participants. The primary outcome of ischemic stroke was seen in 105 patients with a mean follow-up time of 7.7 years. In the Cox models, we found that carotid distensibility (CD), carotid stenosis (CS), and serum interleukin-6 (IL-6) were associated with incident stroke. Adding tertiles of CD, IL-6, and categories of CS to a baseline model that included traditional clinical vascular risk factors resulted in a better model fit than traditional risk factors alone as indicated by goodness-of-fit statistics. Conclusions: In a multiethnic cohort of patients without cerebrovascular disease at baseline, we found that CD, CS, and IL-6 helped predict the occurrence of primary ischemic stroke. Future research could evaluate if these basic ultrasound and serum measurements have implications for primary prevention efforts or clinical trial inclusion criteria.

Ideology, communication and polarization

2021 ◽  
Vol 376 (1822) ◽  
pp. 20200133
Author(s):  
Yoshihisa Kashima ◽  
Andrew Perfors ◽  
Vanessa Ferdinand ◽  
Elle Pattenden
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Political Discourse ◽  
Network Dynamics ◽  
Political Polarization ◽  
Connectionist Model ◽  
Theme Issue ◽  
Social Network Dynamics ◽  
Dynamic Social Networks ◽  
Echo Chamber

Ideologically committed minds form the basis of political polarization, but ideologically guided communication can further entrench and exacerbate polarization depending on the structures of ideologies and social network dynamics on which cognition and communication operate. Combining a well-established connectionist model of cognition and a well-validated computational model of social influence dynamics on social networks, we develop a new model of ideological cognition and communication on dynamic social networks and explore its implications for ideological political discourse. In particular, we explicitly model ideologically filtered interpretation of social information, ideological commitment to initial opinion, and communication on dynamically evolving social networks, and examine how these factors combine to generate ideologically divergent and polarized political discourse. The results show that ideological interpretation and commitment tend towards polarized discourse. Nonetheless, communication and social network dynamics accelerate and amplify polarization. Furthermore, when agents sever social ties with those that disagree with them (i.e. structure their social networks by homophily), even non-ideological agents may form an echo chamber and form a cluster of opinions that resemble an ideological group. This article is part of the theme issue ‘The political brain: neurocognitive and computational mechanisms’.

A network case of knowledge brokering

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joelle Rodway ◽  
Stephen MacGregor ◽  
Alan Daly ◽  
Yi-Hwa Liou ◽  
Susan Yonezawa ◽  
...  
Keyword(s):  
Social Network ◽  
Learning Community ◽  
Knowledge Exchange ◽  
Point Of View ◽  
Network Activity ◽  
Centrality Measures ◽  
Knowledge Brokering ◽  
Content Type ◽  
Knowledge Brokers ◽  
Over Time

PurposeThe purpose of this paper is two-fold: (1) to offer a conceptual understanding of knowledge brokering from a sociometric point-of-view; and (2) to provide an empirical example of this conceptualization in an education context.Design/methodology/approachWe use social network theory and analysis tools to explore knowledge exchange patterns among a group of teachers, instructional coaches and administrators who are collectively seeking to build increased capacity for effective mathematics instruction. We propose the concept of network activity to measure direct and indirect knowledge brokerage through the use of degree and betweenness centrality measures. Further, we propose network utility—measured by tie multiplexity—as a second key component of effective knowledge brokering.FindingsOur findings suggest significant increases in both direct and indirect knowledge brokering activity across the network over time. Teachers, in particular, emerge as key knowledge brokers within this networked learning community. Importantly, there is also an increase in the number of resources exchanged through network relationships over time; the most active knowledge brokers in this social ecosystem are those individuals who are exchanging multiple forms of knowledge.Originality/valueThis study focuses on knowledge brokering as it presents itself in the relational patterns among educators within a social ecosystem. While it could be that formal organizational roles may encapsulate knowledge brokering across physical structures with an education system (e.g. between schools and central offices), these individuals are not necessarily the people who are most effectively brokering knowledge across actors within the broader social network.

Pierre Bourdieu and International Relations

2018 ◽  
Author(s):  
Antonin Cohen
Keyword(s):  
Social Capital ◽  
International Relations ◽  
Social Space ◽  
Pierre Bourdieu ◽  
Golden Thread ◽  
Over Time

Over time, Pierre Bourdieu became an emergent reference in international relations—quite paradoxically, given that Bourdieu himself did not pay much attention to international relations as such. This chapter exhaustively reviews the works of Bourdieu in search of the international, both as a dimension of social capital and as a social space across societies. It then retraces how pioneering scholars used the theory and concepts of Bourdieu to develop their analysis of transnational processes. It also assesses the more recent blossoming of scholarship using Bourdieu in international relations, sometimes at the risk of inconsistency with the theory of Bourdieu. It finally suggests a coherent reconstruction of a theory of transnational fields based on Bourdieu for further research. Throughout the chapter, the notion of field serves as a golden thread to go back to its genealogy, to be found, surprisingly, in international relations.

scholarly journals Temporal Activity Path Based Character Correction in Heterogeneous Social Networks via Multimedia Sources

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Jun Long ◽  
Lei Zhu ◽  
Zhan Yang ◽  
Chengyuan Zhang ◽  
Xinpan Yuan
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Large Scale ◽  
Multimedia Data ◽  
Attribute Information ◽  
Novel Method ◽  
Relationship Network ◽  
Heterogeneous Social Networks ◽  
The Relationship ◽  
Over Time

Vast amount of multimedia data contains massive and multifarious social information which is used to construct large-scale social networks. In a complex social network, a character should be ideally denoted by one and only one vertex. However, it is pervasive that a character is denoted by two or more vertices with different names; thus it is usually considered as multiple, different characters. This problem causes incorrectness of results in network analysis and mining. The factual challenge is that character uniqueness is hard to correctly confirm due to lots of complicated factors, for example, name changing and anonymization, leading to character duplication. Early, limited research has shown that previous methods depended overly upon supplementary attribute information from databases. In this paper, we propose a novel method to merge the character vertices which refer to the same entity but are denoted with different names. With this method, we firstly build the relationship network among characters based on records of social activities participating, which are extracted from multimedia sources. Then we define temporal activity paths (TAPs) for each character over time. After that, we measure similarity of the TAPs for any two characters. If the similarity is high enough, the two vertices should be considered as the same character. Based on TAPs, we can determine whether to merge the two character vertices. Our experiments showed that this solution can accurately confirm character uniqueness in large-scale social network.

Quantifying Virality of Information in Online Social Networks

2012 ◽  
Vol 4 (1) ◽  
pp. 32-45 ◽  
Author(s):  
Abhishek Vaish ◽  
Rajiv Krishna G. ◽  
Akshay Saxena ◽  
Dharmaprakash M. ◽  
Utkarsh Goel
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Online Social Network ◽  
Critical Factors ◽  
Asset Valuation ◽  
Valuation Technique ◽  
Information Item ◽  
Viral Nature ◽  
Over Time

The aim of this research is to propose a model through which the viral nature of an information item in an online social network can be quantified. Further, the authors propose an alternate technique for information asset valuation by accommodating virality in it which not only complements the existing valuation system, but also improves the accuracy of the results. They use a popularly available YouTube dataset to collect attributes and measure critical factors such as share-count, appreciation, user rating, controversiality, and comment rate. These variables are used with a proposed formula to obtain viral index of each video on a given date. The authors then identify a conventional and a hybrid asset valuation technique to demonstrate how virality can fit in to provide accurate results.The research demonstrates the dependency of virality on critical social network factors. With the help of a second dataset acquired, the authors determine the pattern virality of an information item takes over time.

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