A social network analysis of Canadian food insecurity policy actors

2018 ◽  
Vol 79 (2) ◽  
pp. 60-66 ◽  
Author(s):  
Lynn McIntyre ◽  
Geneviève Jessiman-Perreault ◽  
Catherine L. Mah ◽  
Jenny Godley

Purpose: This paper aims to: (i) visualize the networks of food insecurity policy actors in Canada, (ii) identify potential food insecurity policy entrepreneurs (i.e., individuals with voice, connections, and persistence) within these networks, and (iii) examine the political landscape for action on food insecurity as revealed by social network analysis. Methods: A survey was administered to 93 Canadian food insecurity policy actors. They were each asked to nominate 3 individuals whom they believed to be policy entrepreneurs. Ego-centred social network maps (sociograms) were generated based on data on nominees and nominators. Results: Seventy-two percent of the actors completed the survey; 117 unique nominations ensued. Eleven actors obtained 3 or more nominations and thus were considered policy entrepreneurs. The majority of actors nominated actors from the same province (71.5%) and with a similar approach to theirs to addressing food insecurity (54.8%). Most nominees worked in research, charitable, and other nongovernmental organizations. Conclusions: Networks of Canadian food insecurity policy actors exist but are limited in scope and reach, with a paucity of policy entrepreneurs from political, private, or governmental jurisdictions. The networks are divided between food-based solution actors and income-based solution actors, which might impede collaboration among those with differing approaches to addressing food insecurity.

2019 ◽  
Vol 60 (2) ◽  
pp. 363-376
Author(s):  
Tetiana Kostiuchenko ◽  
Inna Melnykovska

Abstract How was the business-state symbiosis in Ukraine sustained throughout the political turbulences of the Orange Revolution and the Revolution of Dignity? Using the method of social network analysis (SNA), we demonstrate how the political – formal and informal – ties of Ukrainian big business to the different branches of state power evolved and what models of state-business relations developed during each presidency. The analysis covers the period of 2007-2018 and focuses on the comparison of the relational structures between political and business elites in Ukraine over a decade. We trace the visibility of various business cliques within political institutions during the last 10 years, and track changes in business-state relations through influential persons, positions, groups and network structures.


2021 ◽  
pp. 160-182
Author(s):  
Olga Popova ◽  
Sergey Suslov

The article is dedicated to the development of the political communities in social networks analysis methods. Main stages of network approach in the political science is described in the research. Researchers review the most significant methods and techniques in the political online communities studies for the last decade. The article shows the contemporary Russian scientists contribution in the development of online communities learning techniques. Networks and social network analysis methods and techniques become universal scientific approaches for several scientific fields. Boundary-transcending trends were critical means of science integration. Researchers present the results of experiment in which evaluate the possibilities of study unobserved political groups using latent Dirichlet allocation (LDA) model. The brief LDA foundation history and possible modifications for social topic modeling based on social networks data are discribed in the review. Using sample from one feed aggregator telegram channel in period of 2020 autumn, the authors display the most valuable topics in the Russian segment of political communication. Also it provides communities ideological preferences. Modified qualitative sociological methods can be used in online political communities discursive features research without any specific computer science techniques. Since about 70% of the Internet data are generated in the social networks, velocity and volume data necessitate new data mining techniques, databases capacity and computation processes. In other words, it provides a big data approach in social network analysis.


PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251472
Author(s):  
Immaculate Sabelile Muthathi ◽  
Mary Kawonga ◽  
Laetitia Charmaine Rispel

Background Within the context of universal health coverage (UHC), South Africa has embarked on a series of health sector reforms. The implementation of the Ideal Clinic Realisation and Maintenance (ICRM) programme is a major UHC reform. Cooperative governance is enshrined in South Africa’s Constitution, with health a concurrent competency of national and provincial government. Hence, effective inter-governmental relations (IGR) are essential for the ICRM programme implementation. Aim The aim of the study was to measure the cohesion of IGR, specifically consultation, support and information sharing, across national, provincial and local government health departments in the ICRM programme implementation. Materials and methods Using Provan and Milward’s theory on network effectiveness, this study was a whole network design social network analysis (SNA). The study was conducted in two districts in Gauteng (GP) and Mpumalanga (MP) provinces of South Africa. Following informed consent, we used both an interview schedule and a network matrix to collect the social network data from health policy actors in national, provincial and local government. We used UCINET version 6.619 to analyse the SNA data for the overall network cohesion and cohesion within and between the government spheres. Results The social network analysis revealed non-cohesive relationships between the different spheres of government. In both provinces, there was poor consultation in the ICRM programme implementation, illustrated by the low densities of seeking advice (GP = 15.6%; MP = 24.4%) and providing advice (GP = 14.1%; MP = 25.1%). The most cohesive relationships existed within the National Department of Health (density = 66.7%), suggesting that national policy actors sought advice from one another, rather than from the provincial health departments. A density of 2.1% in GP, and 12.5% in MP illustrated the latter. Conclusion The non-cohesive relationships amongst policy actors across government spheres should be addressed in order to realise the benefits of cooperative governance in implementing the ICRM programme.


2018 ◽  
Vol 33 (3) ◽  
pp. 321-337 ◽  
Author(s):  
Tomás Baviera

Candidates, parties, media and citizens have the same ability to post tweets. For this reason, mapping the dynamics of interaction among users is essential to evaluate the processes of influence in an electoral campaign. However, characterising these aspects requires methodologies that consider the interconnections generated by users globally. The discipline of social network analysis provides the concepts of centrality and modularity, both very suitable for the context of network communication. This article analyses the political conversation on Twitter during the 2015 and 2016 General Elections in Spain, in which four candidates with significant popularity in the electorate participated. Two corpora of 8.9 million and 9.7 million tweets were collected from each campaign, respectively, to analyse the networks of mentions and retweets. The network of mentions appears more blurred than that of retweets, allowing us to better estimate users’ partisan preference. The graphs of the network of retweets show a strong internal activity within clusters, and the proximity between them reflects the ideological axis of each party.


2019 ◽  
Vol 6 (1) ◽  
pp. 205395171983523 ◽  
Author(s):  
Emad Khazraee

The fallacy of premature designations such as “Iran's Twitter Revolution” can be attributed to the empirical gap in our knowledge about such sociotechnical phenomena in non-Western societies. To fill this gap, we need in-depth analyses of social media use in those contexts and to create detailed maps of online public environments in such societies. This paper aims to present such cartography of the political landscape of Persian Twitter by studying the case of Iran's 2013 presidential election. The objective of this study is twofold: first, to fill the empirical gap in our knowledge about Twitter use in Iran, and second, to develop computational methods for studying Persian Twitter (e.g., effective methods for analyzing Persian text) and identify the best methods for addressing different issues (e.g., topic detection and sentiment analysis). During Iran's 2013 presidential election, three million tweets were collected and analyzed using social network analysis and machine learning. The findings provide a more nuanced view of the political landscape of Persian Twitter and identify patterns in accordance with or in contrast to those identified in the English-speaking Twittersphere around the 2013 presidential election. Persian Twitter was dominated by micro-celebrities, whereas institutional elites dominated English discourse about Iran on Twitter. The results also illustrate that Persian Twitter in 2013 was predominantly in favor of reformists. Finally, this study demonstrates that sentiment analysis toward political name entities can be used efficiently for mapping the political landscape of conversation on Twitter.


2021 ◽  
Vol 2 (4) ◽  
pp. 709-731
Author(s):  
Huu Dat Tran

(1) The study investigated the social network surrounding the hashtags #maga (Make America Great Again, the campaign slogan popularized by Donald Trump during his 2016 and 2020 presidential campaigns) and #trump2020 on Twitter to better understand Donald Trump, his community of supporters, and their political discourse and activities in the political context of the 2020 US presidential election. (2) Social network analysis of a sample of 220,336 tweets from 96,820 unique users, posted between 27 October and 2 November 2020 (i.e., one week before the general election day) was conducted. (3) The most active and influential users within the #maga and #trump2020 network, the likelihood of those users being spamming bots, and their tweets’ content were revealed. (4) The study then discussed the hierarchy of Donald Trump and the problematic nature of spamming bot detection, while also providing suggestions for future research.


2020 ◽  
Vol 12 (13) ◽  
pp. 5440
Author(s):  
Jie Yin ◽  
Yahua Bi ◽  
Yingchao Ji

Tourism cooperation is an essential element for tourism development in China-ASEAN countries and has made a significant economic contribution to destinations. This study investigates the structure of tourism cooperation in China-ASEAN relations and identifies a set of factors that affect tourism cooperation from a network perspective. By employing social network analysis, the results indicate that the scale of cooperation is small, and the efficiency is not high, although the restrictions on cooperation between countries are reduced. The findings also indicate that differences in the political system, security, population density, and language can promote tourism cooperation, while differences in governance, income, and consumption level impede tourism cooperation. The research results may assist China-ASEAN countries to formulate tourism strategies suitable for international cooperation and national differences.


2021 ◽  
Vol 49 (2) ◽  
pp. 414-445
Author(s):  
Evangelia Petridou ◽  
Per Becker ◽  
Jörgen Sparf

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