scholarly journals The ever-changing face of Chinese Interpreting Studies: a social network analysis

2015 ◽  
Author(s):  
Ziyun Xu
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Productivity ◽  
Academic Research ◽  
Research Impact ◽  
Research Community ◽  
Regional Level ◽  
The Past ◽  
Academic Influence

As the discipline of Translation and Interpreting Studies (TIS) has continued to expand rapidly over the past twenty years, scientometric research has been increasingly applied to analyze its trends and patterns. Drawing inspiration from Social Network Analysis, this study aims to quantify academic research impact and identify patterns of influence at an institutional and regional level in Chinese Interpreting Studies (CIS), by seeking answers to the following questions: Which are the most influential publications? Which institutions and regions carry the most weight? How have their respective levels of influence evolved over time? By analyzing a near-exhaustive corpus of 59,303 citations from CIS literature, the study reveals that most of the influential publications are monographs and theoretical in nature, though many Chinese textbooks on interpreting are also highly influential. It also finds that an institution’s ranking in research productivity does not necessarily translate into high academic influence, and geographical proximity does not determine whether neighboring regions belong to the same research community.

scholarly journals The ever-changing face of Chinese Interpreting Studies: a social network analysis

2015 ◽  
Author(s):  
Ziyun Xu
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Productivity ◽  
Academic Research ◽  
Research Impact ◽  
Research Community ◽  
Regional Level ◽  
The Past ◽  
Academic Influence

As the discipline of Translation and Interpreting Studies (TIS) has continued to expand rapidly over the past twenty years, scientometric research has been increasingly applied to analyze its trends and patterns. Drawing inspiration from Social Network Analysis, this study aims to quantify academic research impact and identify patterns of influence at an institutional and regional level in Chinese Interpreting Studies (CIS), by seeking answers to the following questions: Which are the most influential publications? Which institutions and regions carry the most weight? How have their respective levels of influence evolved over time? By analyzing a near-exhaustive corpus of 59,303 citations from CIS literature, the study reveals that most of the influential publications are monographs and theoretical in nature, though many Chinese textbooks on interpreting are also highly influential. It also finds that an institution’s ranking in research productivity does not necessarily translate into high academic influence, and geographical proximity does not determine whether neighboring regions belong to the same research community.

The ever-changing face of Chinese Interpreting Studies

Target ◽  
2017 ◽  
Vol 29 (1) ◽  
pp. 7-38 ◽  
Author(s):  
Ziyun Xu
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Productivity ◽  
Academic Research ◽  
Research Impact ◽  
Institutional Level ◽  
The Past ◽  
Academic Influence ◽  
Over Time

As the discipline of Translation and Interpreting Studies (TIS) has continued to expand rapidly over the past twenty years, scientometric research has been applied increasingly often to analyse its trends and patterns. Drawing inspiration from Social Network Analysis (SNA), this study aims to quantify academic research impact and identify patterns of influence at an institutional level in Chinese Interpreting Studies (CIS), by seeking answers to the following questions: Which are the most influential publications? Which institutions carry the most weight? How have their respective levels of influence evolved over time? By analysing a near-exhaustive corpus of 59,303 citations from CIS literature, the study reveals that the majority of influential publications are monographs and theoretical in nature, though many Chinese textbooks on interpreting are also highly influential. It also finds that an institution’s ranking in research productivity does not necessarily translate into high academic influence.

scholarly journals Analysis of Social Phenomenon on Tattoo Using Big Data and Social Network Analysis - News texts for the last year as collated -

2021 ◽  
Vol 27 (5) ◽  
pp. 1139-1145
Author(s):  
Ran-Sug Seo
Keyword(s):  
Big Data ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Academic Research ◽  
Eigenvector Centrality ◽  
Social Phenomena ◽  
The Past ◽  
The Social ◽  
Newspaper Articles

The purpose of this study was to identify the social phenomena of tattoo, which have been of constant interest in our society, through analysis of social networks collected from big data on what the social phenomena implied in keywords emphasized in newspaper articles over the past year. To this end, by analyzing keywords about tattoos that frequently appeared in newspaper articles, we could see what the main interests of social phenomena related to tattoos were. Data on tattoos were collected from newspaper articles over the past year and analyzed how they formed meaning regarding the relationship structure and centrality between the keywords at issue through social network analysis. These findings provide basic data on social discussions and policy directions related to tattoos in practice and discussions related to ways to improve them. This study is an extension from existing quantitative research by analyzing the social phenomena of tattoos through Bigdata and social network analysis. Apart from statistical surveys or subjective qualitative research, we have approached them with content analysis using big data and social network analysis. The conclusion of this study is as follows. First, as a result of analyzing the word cloud regarding tattoos, it was confirmed that “rose” and “300” were the most prominent, and there were keywords that could analyze various other social phenomena. Second, as a result of analysis by connection centrality, it was proved that the social interest and popularity of tattoos increased. Third, as a result of analysis by eigenvector centrality, the popularity of tattoos was proved. It objectified academic research by attempting research from a different perspective from the analysis of research trends and provided visualized research results of readers.

Social network analysis and data visualization of MIS international collaboration in Taiwan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ting Chuang ◽  
Yi-Hsi Chen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
International Collaboration ◽  
Research Productivity ◽  
Research Collaboration ◽  
Clustering Algorithms ◽  
The United States ◽  
Content Type ◽  
Collaboration Patterns

PurposeThe purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.Design/methodology/approachThe authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.FindingsThe authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.Originality/valueThis study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

Network Perspectives on the Past: Tackling the Challenges

2016 ◽  
Author(s):  
Tom Brughmans ◽  
Anna Collar
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relations ◽  
Social Life ◽  
Academic Career ◽  
Special Method ◽  
The Past ◽  
Full Diversity ◽  
Strength Of Weak Ties

As his keynote address to the 1990 Sunbelt Social Networks conference, Mark Granovetter presented a paper entitled ‘The Myth of Social Network Analysis as a Special Method in the Social Sciences’ (Granovetter 1990). In it, he described how the popular social network theory he proposed, ‘The Strength of Weak Ties’ (Granovetter 1973), was like a spectre that haunted his academic career: although he subsequently pursued other research interests, he found that ‘as I got more deeply into any subject, network ideas kept coming in the back door’. He concluded that social network analysis (SNA) is not a ‘special’ method in social science, because ‘no part of social life can be properly analysed without seeing how it is fundamentally embedded in networks of social relations’ (Granovetter 1990: 15). However, he noted that to many, SNA is an alien concept: ‘we need to remember that there are many scholars outside the house of social network analysis who think in a relational way but don’t see the kinship with network methods and ideas’ (Granovetter 1990: 15). This observation echoes the current position of network studies in archaeology and history. Few would argue that relationships between social entities are not important for understanding past social processes. However, more explicit application of network theories and methods is not yet a mainstream part of our disciplines. Although it is the case that some researchers are not aware of the advantages such perspectives might offer, the current ‘niche’ status of network applications in archaeological and historical research relates to a more general misperception: that network concepts and methodologies per se are simply not appropriate for use in research in these disciplines. This volume aims to address both issues: the contributions in this volume demonstrate both the enormous potential of network methodologies, and also—and perhaps more importantly—acknowledge and address a range of perceived problems and reservations relating to the application of network perspectives to the study of the past, thereby encouraging and enabling their wider use in archaeology and history. The full diversity of network perspectives has only been introduced in our disciplines relatively recently.

scholarly journals Research on China’s Green Finance Policies Based on Text Mining

2020 ◽  
Vol 185 ◽  
pp. 02024
Author(s):  
Yuqing Liao ◽  
Jingliang Chen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
High Frequency ◽  
Policy Documents ◽  
Analysis Techniques ◽  
The Past ◽  
Word Cloud ◽  
Green Finance ◽  
Occurrence Matrix

Based on the green finance policies in China from 2017 to 2019, this paper extracts feature and high-frequency words from policy documents, uses word cloud diagram, co-occurrence matrix and social network analysis techniques to quantitatively analyse the information contained in the green finance policies over the past three years and highlights the hot issues in question, thus providing a multi-layered and wideranging pathway for facilitating the orderly development of green finance industries across China.

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