scholarly journals Trends in distance education research: A content analysis of journals 2009-2013

2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Aras Bozkurt ◽  
Ela Akgun-Ozbek ◽  
Sibel Yilmazel ◽  
Erdem Erdogdu ◽  
Hasan Ucar ◽  
...  
Keyword(s):  
Distance Education ◽  
Education Research ◽  
Content Analysis ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Descriptive Analysis ◽  
Research Areas ◽  
Current Trends ◽  
E Learning

<p>This study intends to explore the current trends in the field of distance education research during the period of 2009-2013. The trends were identified by an extensive review of seven peer reviewed scholarly journals: <em>The American Journal of Distance Education</em> (AJDE), <em>Distance Education</em> (DE), <em>The European Journal of Open, Distance and e-Learning</em> (EURODL), <em>The Journal of Distance Education</em> (JDE), <em>The Journal of Online Learning and Technology</em> (JOLT), <em>Open Learning: The Journal of Open, Distance and e-Learning</em> (OL) and <em>The International Review of Research in Open and Distributed Learning</em> (IRRODL). A total of 861 research articles was reviewed. Mainly content analysis was employed to be able to analyze the current research. Also, a social network analysis (SNA) was used to interpret the interrelationship between keywords indicated in these articles. Themes were developed and the content of the articles in the selected journals were coded according to categories derived from earlier studies. The results were interpreted using descriptive analysis (frequencies) and social network analysis. The reporting of the results were organized into the following categories: research areas, theoretical and conceptual frameworks, variables, methods, models, strategies, data collection and analysis methods, and the participants. The study also identified the most commonly used keywords, and the most frequently cited authors and studies in distance education. The findings obtained in this study may be useful in the exploration of potential research areas and identification of neglected areas in the field of distance education.  </p>

Current Trends and Future Directions in Knowledge Management in Construction Research Using Social Network Analysis

Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 599
Author(s):  
Sepani Senaratne ◽  
Muhandiramge Nimashi Navodana Rodrigo ◽  
Xiaohua Jin ◽  
Srinath Perera
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Construction Projects ◽  
Knowledge Flows ◽  
Future Research ◽  
Research Areas ◽  
Current Trends ◽  
Improved Performance

The growing interest in Knowledge Management (KM) has led to increased attention to Social Network Analysis (SNA) as a tool to map the relationships in networks. SNA can be used to evaluate knowledge flows between project teams, contributing to collaborative working and improved performance. Similarly, it has the potential to be used for construction projects and organisations. This paper aims at identifying current trends and future research directions related to using SNA for KM in construction. A systematic review and thematic analysis were used to critically review the existing studies and identify potential research areas in construction specifically related to research approaches and explore the possibilities for extension of SNA in KM. The findings revealed that there are knowledge gaps in research approaches with case study-based research involving external stakeholders, collaborations, development of communication protocols, which are priority areas identified for future research. SNA in KM related to construction could be extended to develop models that capture both formal and informal relationships as well as the KM process in pre-construction, construction, and post-construction stages to improve the performance of projects. Similarly, SNA can be integrated with methodological concepts, such as Analytic Hierarchy Process (AHP), knowledge broker, and so forth, to improve KM processes in construction. This study identifies potential research areas that provide the basis for stakeholders and academia to resolve current issues in the use of SNA for KM in construction.

scholarly journals Gossip at one’s fingertips: Predictors of celebrity news on Twitter

Journalism ◽  
2018 ◽  
Vol 21 (5) ◽  
pp. 707-726
Author(s):  
Yan Yan ◽  
Wanjiang Zhang
Keyword(s):  
Content Analysis ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
News Coverage ◽  
Capitalist Society ◽  
Twitter Account ◽  
Celebrity News

The present study collected 2223 tweets of news about the Top 100 celebrities from People Magazine’s Twitter account during the year 2016. A combination of content analysis and social network analysis was used to examine celebrity attributes, news features, and the relationships between celebrities and news topics. Results indicated that news agendas and audiences’ responses were highly different. News coverage was primarily determined by news features, yet audiences cared only about big stars. Regular topics centered on the themes of celebrity news. The celebrity-by-topic network was topic-driven rather than human-driven, demonstrating the nature of the celebrity industry as an embodiment of capitalist society.

Visualizing Co-Authorship Social Networks and Collaboration Recommendations With CNARe

2018 ◽  
pp. 173-188
Author(s):  
Michele A. Brandão ◽  
Matheus A. Diniz ◽  
Guilherme A. de Sousa ◽  
Mirella M. Moro
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Large Scale ◽  
Online Tool ◽  
Strength Of Ties ◽  
E Learning

Studies have analyzed social networks considering a plethora of metrics for different goals, from improving e-learning to recommend people and things. Here, we focus on large-scale social networks defined by researchers and their common published articles, which form co-authorship social networks. Then, we introduce CNARe, an online tool that analyzes the networks and present recommendations of collaborations based on three different algorithms (Affin, CORALS and MVCWalker). Through visualizations and social networks metrics, CNARe also allows to investigate how the recommendations affect the co-authorship social networks, how researchers' networks are in a central and eagle-eye context, and how the strength of ties behaves in large co-authorship social networks. Furthermore, users can upload their own network in CNARe and make their own recommendation and social network analysis.

Network Analysis for Economics and Management Studies

2016 ◽  
pp. 1-60 ◽  
Author(s):  
Lucio Biggiero
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Formation ◽  
Competitive Equilibrium ◽  
Group Structure ◽  
Network Modeling ◽  
Descriptive Analysis ◽  
Economic Networks ◽  
Main Research

Sociology and other social sciences have employed network analysis earlier than management and organization sciences, and much earlier than economics, which has been the last one to systematically adopt it. Nevertheless, the development of network economics during last 15 years has been massive, alongside three main research streams: strategic formation network modeling, (mostly descriptive) analysis of real economic networks, and optimization methods of economic networks. The main reason why this enthusiastic and rapidly diffused interest of economists came so late is that the most essential network properties, like externalities, endogenous change processes, and nonlinear propagation processes, definitely prevent the possibility to build a general – and indeed even partial – competitive equilibrium theory. For this paradigm has dominated economics in the last century, this incompatibility operated as a hard brake, and presented network analysis as an inappropriate epistemology. Further, being intrinsically (and often, until recent times, also radically) structuralist, social network analysis was also antithetic to radical methodological individualism, which was – and still is – economics dominant methodology. Though culturally and scientifically influenced by economists in some fields, like finance, banking and industry studies, scholars in management and organization sciences were free from “neoclassical economics chains”, and therefore more ready and open to adopt the methodology and epistemology of social network analysis. The main and early field through which its methods were channeled was the sociology of organizations, and in particular group structure and communication, because this is a research area largely overlapped between sociology and management studies. Currently, network analysis is becoming more and more diffused within management and organization sciences. Mostly descriptive until 15 years ago, all the fields of social network analysis have a great opportunity of enriching and developing its methods of investigation through statistical network modeling, which offers the possibility to develop, respectively, network formation and network dynamics models. They are a good compromise between the much more powerful agent-based simulation models and the usually descriptive (or poorly analytical) methods.

Peer Assistance and Interaction in an Online Forum

2011 ◽  
pp. 118-130
Author(s):  
Ugur Kale
Keyword(s):  
Content Analysis ◽  
Instructional Design ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Peer Interaction ◽  
Graduate Level ◽  
Online Forum ◽  
Peer Assistance ◽  
To Receive

This study examines peer interaction and peer assistance observed in on an online forum, part of a graduate level instructional design course during the 2008 spring academic term. It incorporates both content analysis and social network analysis techniques. The content analysis results showed that the four types of peer assistance adopted from an existing framework were adequate to categorize the peer assistance that the students received during the study. Students tended to receive more Reflective assistance from their peers if their reading reflections provided high relevance to the course projects. Social network analysis results revealed that while 70% of the students provided peer assistance to one another, they were less likely to go beyond the course requirement of posting toward to end of the semester. Also, a further analysis demonstrated how SNA approach may help examine the influences of actor attributes on their observed communication.

scholarly journals Linking Quantitative and Qualitative Network Approaches: A Review of Mixed Methods Social Network Analysis in Education Research

2020 ◽  
Vol 44 (1) ◽  
pp. 244-268 ◽  
Author(s):  
Dominik E. Froehlich ◽  
Sara Van Waes ◽  
Hannah Schäfer
Keyword(s):  
Education Research ◽  
Social Network ◽  
Mixed Methods ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Mixed Methods Research ◽  
Qualitative Approaches ◽  
Research Questions ◽  
Network Approaches

Social network analysis (SNA) is becoming a prevalent method in education research and practice. But criticism has been voiced against the heavy reliance on quantification within SNA. Recent work suggests combining quantitative and qualitative approaches in SNA—mixed methods social network analysis (MMSNA)—as a remedy. MMSNA is helpful for addressing research questions related to the formal or structural side of relationships and networks, but it also attends to more qualitative questions such as the meaning of interactions or the variability of social relationships. In this chapter, we describe how researchers have applied and presented MMSNA in publications from the perspective of general mixed methods research. Based on a systematic review, we summarize the different applications within the field of education and learning research, point to potential shortcomings of the methods and its presentation, and develop an agenda to support researchers in conducting future MMSNA research.

Social network analysis of a gamified e-learning course: Small-world phenomenon and network metrics as predictors of academic performance

2016 ◽  
Vol 60 ◽  
pp. 312-321 ◽  
Author(s):  
Luis de-Marcos ◽  
Eva García-López ◽  
Antonio García-Cabot ◽  
José-Amelio Medina-Merodio ◽  
Adrián Domínguez ◽  
...  
Keyword(s):  
Academic Performance ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Small World ◽  
E Learning ◽  
Network Metrics ◽  
Predictors Of Academic Performance
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