The impact of social network dynamics on engagement in drug use reduction programs among men and women who use drugs

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’.

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The Politics of Communist Economic Reform

The Emergence of Organizations and Markets ◽

10.23943/princeton/9780691148670.003.0009 ◽

2012 ◽

Author(s):

John F. Padgett

Keyword(s):

Social Network ◽

Economic Reform ◽

Network Dynamics ◽

Mao Zedong ◽

The Political ◽

Mikhail Gorbachev ◽

East European ◽

Social Network Dynamics ◽

Nikita Khrushchev ◽

Political Economic

This chapter compares the political, economic, and social-network dynamics of major economic reform campaigns within communism itself by Joseph Stalin, Nikita Khrushchev, Mao Zedong, Deng Xiaoping, and Mikhail Gorbachev. Over their histories, Soviet, Chinese, and East European communisms frequently had tried to reform themselves economically in a wide variety of ways. The dynamics of economic reform in the climactic 1980s were not as different from what had preceded it as is commonly assumed. It was the outcome more than the process that differed. Hence, the chapter analyzes the transition from communism to “capitalism” not from the outside perspective of capitalism but from the internal perspective of communism.

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Modeling and Analysis of Social Network Dynamics on the Macro-Level in View of the Customer-Centric Concept

2018 IEEE 20th Conference on Business Informatics (CBI) ◽

10.1109/cbi.2018.10061 ◽

2018 ◽

Author(s):

O.A. Tsukanova ◽

S.V. Maltseva ◽

K.E. Fedorov

Keyword(s):

Social Network ◽

Network Dynamics ◽

Macro Level ◽

Modeling And Analysis ◽

Social Network Dynamics

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Mouse Social Network Dynamics and Community Structure are Associated with Plasticity-Related Brain Gene Expression

Frontiers in Behavioral Neuroscience ◽

10.3389/fnbeh.2016.00152 ◽

2016 ◽

Vol 10 ◽

Cited By ~ 19

Author(s):

Cait M. Williamson ◽

Becca Franks ◽

James P. Curley

Keyword(s):

Gene Expression ◽

Community Structure ◽

Social Network ◽

Network Dynamics ◽

Brain Gene Expression ◽

Social Network Dynamics

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Social network dynamics throughout clinical training—Distance matters

Medical Education ◽

10.1111/medu.14421 ◽

2020 ◽

Author(s):

Layla Badawy ◽

Priyanka Oza ◽

Rohan Shankarghatta ◽

Elisa Merlini

Keyword(s):

Social Network ◽

Clinical Training ◽

Network Dynamics ◽

Social Network Dynamics

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Dynamics of stakeholder engagement in mega transport infrastructure projects

International Journal of Managing Projects in Business ◽

10.1108/ijmpb-09-2018-0175 ◽

2019 ◽

Vol 13 (7) ◽

pp. 1465-1495 ◽

Cited By ~ 2

Author(s):

Mehmet Erkul ◽

Ibrahim Yitmen ◽

Tahir Celik

Keyword(s):

Social Network ◽

Stakeholder Engagement ◽

Structural Equation ◽

Project Success ◽

Network Dynamics ◽

Transport Infrastructure ◽

Infrastructure Projects ◽

Content Type ◽

Stakeholder Satisfaction ◽

Social Network Dynamics

Purpose The purpose of this paper is to investigate the practice of stakeholder engagement as a social network dynamics for stakeholder satisfaction and project success in the lifecycle of mega transport infrastructure projects (MTIPs). Design/methodology/approach Hypotheses indicating the positive relationships between stakeholders’ effective attributes, stakeholder engagement as social network dynamics and project success through stakeholders’ satisfaction have been developed. Based on a questionnaire survey and semi-structured interviews, responses have been gathered from the representative groups and organizations on their social network dynamics for their satisfaction and project success. A hypothesized structural equation model has been tested using AMOS statistical software package. Findings The analysis highlighted the engagement of the stakeholders within the strategic intents of the project with the public needs and expectations. The model depicts the processes of building social network models based on the capturing of the project’s data in relation to the stakeholders’ communication and satisfaction across the key issues for success in the lifecycle of MTIP. Practical implications The model is applicable on most MTIP with a diverse stakeholder base and the underlying complexity associated with the community participation and consultation processes. The model will also support wider stakeholder engagement in the planning of MTIP with optimal operationalization and service delivery from a community perspective. Originality/value The research involves an approach for rationalizing the stakeholder engagement policies of the MTIPs by providing an empirically grounded model simultaneously linking various aspects of stakeholder effective attributes, stakeholder engagement and their relationships to stakeholder satisfaction and project success in MTIPs.

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