scholarly journals Structure and Formation Mechanism of China-ASEAN Tourism Cooperation

2020 ◽  
Vol 12 (13) ◽  
pp. 5440
Author(s):  
Jie Yin ◽  
Yahua Bi ◽  
Yingchao Ji
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Population Density ◽  
Political System ◽  
Essential Element ◽  
The Political ◽  
National Differences ◽  
Economic Contribution ◽  
Asean Countries

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.

Sustaining Business-State Symbiosis in Times of Political Turmoil: the Case of Ukraine 2007-2018

2019 ◽  
Vol 60 (2) ◽  
pp. 363-376
Author(s):  
Tetiana Kostiuchenko ◽  
Inna Melnykovska
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Political Institutions ◽  
The Political ◽  
Business Elites ◽  
Relational Structures ◽  
Orange Revolution ◽  
State Relations ◽  
Political Turmoil

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.

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
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Nongovernmental Organizations ◽  
Food Insecurity ◽  
The Political ◽  
Policy Entrepreneurs ◽  
Policy Actors ◽  
Political Landscape ◽  
Potential Food

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.

scholarly journals Network Analysis of Political Internet Communities: from Formalized to «Unobserved» Groups

2021 ◽  
pp. 160-182
Author(s):  
Olga Popova ◽  
Sergey Suslov
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Communities ◽  
Latent Dirichlet Allocation ◽  
The Political ◽  
Analysis Methods ◽  
Methods And Techniques ◽  
Political Communities

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.

scholarly journals Influence in the political Twitter sphere: Authority and retransmission in the 2015 and 2016 Spanish General Elections

2018 ◽  
Vol 33 (3) ◽  
pp. 321-337 ◽  
Author(s):  
Tomás Baviera
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Communication ◽  
The Political ◽  
Electoral Campaign ◽  
Political Conversation ◽  
General Elections

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.

scholarly journals Comparative Study of Asean Countries Research Productivity in Library Science

Webology ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 371-388
Author(s):  
Cecep Ibrahim ◽  
Ria Hardiyati ◽  
Winda Anesya Ayunda ◽  
Rahmat Fadhli
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Linear Regression ◽  
Southeast Asia ◽  
Information Science ◽  
Library Science ◽  
Regression Test ◽  
Asean Countries

Library science is one of the fastest-growing fields of knowledge, especially in Southeast Asian countries. This study aims to determine library science publications in Southeast Asia with approaches, namely bibliometrics, social network analysis, almetrics, and linear regression test. This study's data were taken from the Scopus web to obtain bibliographic data from library science publications in ten countries published in 1960-2019. Bibliometrics analysis uses Microsoft Excel calculations, mapping/scientometrics uses Vos viewer and Gephi, while altmetrics analysis uses altmetric.com. Based on the bibliometric analysis, the results showed that the most productive country is Malaysia, with 287 articles. The most sponsored publication’s country is Malaysia, with 57 articles. International journals that are popular as destinations for publication of library science articles in Southeast Asia are the Malaysian Journal of Library and Information Science (MJLIS). The country that has the most impact factor for citation is Singapore, with 4.922 citations. The country with the highest level of collaboration is Malaysia, with a total collaboration of 243 articles. The research results are based on social network analysis that the country that has the highest influence is Malaysia with a degree centrality (DC) of 301, closeness centrality (CC) of 0.61, and between centrality (BC) 0.66. The results of the study are based on altmetrics analysis. The country with the most shares/mentions on social media is Singapore, with 5.223 shares/mentions, the second is Malaysia 1467 shares/mentions. Meanwhile, based on the linear regression test that there is an influence between social media and citation, it is indicated by the Sig value of 0.001. Meanwhile, the large correlation between social media and citations was 97.8%.

scholarly journals The Problem of Complexity in the Modern Migration: «Power in Networks» or «Power of Networks»

2016 ◽  
pp. 130-135
Author(s):  
V A Osipov
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Political System ◽  
Modern World ◽  
Specific Character ◽  
Illegal Migration ◽  
Political Processes

This article aims at the modern immigration problems through the concept of complexity. The paper includes the case study of social network analysis of illegal migration in Greece made and visualized in UCINET program v. 6.205 (Net-draw v. 2.097). The specific character of modern immigration reflects the number of problems and features of the modern world as well as political processes. Due to this the article touches upon crucial questions such as what is a place and role of a state in conditions of Instability and nonlinearity on supranational and domestic levels; are the mechanisms of political system able to maintain homeostatic balance and what is the role of the rapid and widespread network types of relations and structures; and others.

scholarly journals Studying the Community of Trump Supporters on Twitter during the 2020 US Presidential Election via Hashtags #maga and #trump2020

2021 ◽  
Vol 2 (4) ◽  
pp. 709-731
Author(s):  
Huu Dat Tran
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Presidential Election ◽  
Political Context ◽  
Future Research ◽  
The Political ◽  
Donald Trump ◽  
The Social ◽  
Us Presidential Election

(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.

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