Examining User Participation and Network Structure via an Analysis of a Twitter-Supported Conference Backchannel

2018 ◽  
Vol 57 (5) ◽  
pp. 1160-1185
Author(s):  
Quan Xie ◽  
Tian Luo
Keyword(s):  
Communication Network ◽  
Social Network ◽  
Network Analysis ◽  
Learning Community ◽  
Opinion Leader ◽  
User Participation ◽  
Network Density ◽  
Key Variables ◽  
Practical Implications ◽  
Significant Factors

This study aimed to examine the scholarly community’s authentic use of Twitter at a professional conference, #ICIS2016, and to investigate how Twitter supports the conference learning community by examining users’ levels of participation in Twitter-enabled conference backchannels and the overall structure of this communication network. We also explored how individuals can better engage in the Twitter-based conference community via revealing the primary characteristics of the central users within the network and studying the significant factors that impact the central status of users. Through an in-depth social network analysis and statistical path analysis, our data revealed users’ varying levels of participation and a relatively low network density, which may suggest participants’ novelty of using Twitter as a conference backchannel. The data further indicated three types of central users: interaction initiator, opinion leader, and conversation bridge, as well as unveiling the relationships among several key variables impacting the central status of a user. Discussion and practical implications are provided.

Communication Network Analysis of Project Teams in Korean Building Constructions

2013 ◽  
Vol 357-360 ◽  
pp. 2338-2341 ◽  
Author(s):  
Jae Yeob Kim ◽  
Sang Tae No ◽  
Yong Kyu Park
Keyword(s):  
Communication Network ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Construction Project ◽  
Project Teams ◽  
Degree Centrality ◽  
Analysis Program ◽  
Team Members ◽  
Communication Frequency

This study used social network analysis (SNA) in order to analyze communication relationship between project team members in typical cases of Korean building constructions. Data was collected by conducting a survey from key members of construction project teams. We analyzed and digitized degree centrality by using Netminer, a SNA analysis program. According to the result of analysis in communication frequency, intermediate managers such as construction deputy managers were shown the highest and architectural designers were shown the lowest. With respect to communication credibility, construction managers were shown the highest and architectural designers were shown to be low. We discovered that intermediate managers and construction managers of the construction teams play important role in the communication of project teams.

Inter-provincial correlations of agricultural GHG emissions in China based on social network analysis methods

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiansheng Qu ◽  
Jinyu Han ◽  
Lina Liu ◽  
Li Xu ◽  
Hengji Li ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Temporal Trends ◽  
Ghg Emissions ◽  
Policy Implications ◽  
Content Type ◽  
Ghg Reduction ◽  
And Cluster Analysis ◽  
Practical Implications

PurposeThe purpose of this paper is to explore the heterogeneity and correlations of agricultural greenhouse gas (GHG) emissions among provinces in China, and then policy implications are proposed.Design/methodology/approachAfter agricultural GHG accounting and a pre-analysis of inter-provincial heterogeneity, improved gravity model and the Social Network Analysis (SNA) methods are introduced to construct the network, being carried out from three aspects of the whole network, individual provincial characteristics and cluster analysis.Findings(1) There are significant regional variations in agricultural GHG scale among provinces owing to the layout of agricultural production, and the temporal trends show that the direction and speed of agricultural GHG scale change vary among provinces; (2) In terms of inter-provincial correlations, there exists a complex spatial network of agricultural GHG among provinces, which tends to be more complex, intensive and stable, while the status of the provinces in the network also has gradually become more balanced. All provinces played their respective roles in the four clusters of the network with agricultural layout and comparative advantages, and the distribution has continuously optimized.Practical implicationsThe inter-provincial network characteristics of agricultural GHG emissions and its evolution have practical implications for differentiated and coordinated agricultural GHG reduction policies at the provincial levels.Originality/valueThis paper innovatively study inter-provincial agricultural GHG correlations in China with the SNA methods used to study economic and social connections in the past. There is some originality in the introduction of network theory and application of the SNA methods, which can provide some reference for researches in similar fields.

Are you passing along something true or false? Dissemination of social media messages about genetically modified organisms

2020 ◽  
pp. 096366252096674
Author(s):  
Qian Xu ◽  
Yunya Song ◽  
Nan Yu ◽  
Shi Chen
Keyword(s):  
Social Media ◽  
Network Analysis ◽  
Structural Stability ◽  
Network Structure ◽  
Genetically Modified Organisms ◽  
Genetically Modified ◽  
Network Density ◽  
Media Messages ◽  
Practical Implications

Using network analysis, this study investigates how information veracity and account verification influence the dissemination of information in the context of discourse about genetically modified organisms on social media. We discovered that misinformation and true information about genetically modified organisms demonstrated different dissemination patterns on social media. In general, the dissemination networks of misinformation about genetically modified organisms were found to have higher structural stability than those of true information about genetically modified organisms, as shown by the denser network structure with fewer distinct subgroups residing within the dissemination networks. More importantly, unverified account status significantly boosted the dissemination of misinformation by increasing network density. In addition, we found that the posts about genetically modified organisms from unverified accounts received more reposts and had more layers of information relay than those from the verified accounts. Theoretical and practical implications of these findings on combating misinformation are discussed in the article.

Mobility and structural change through traumatic organizational events

2014 ◽  
Vol 10 (3) ◽  
pp. 382-408 ◽  
Author(s):  
R. Drew Sellers ◽  
Timothy J. Fogerty ◽  
Larry M. Parker
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Professional Service ◽  
Public Accounting ◽  
Content Type ◽  
The Public ◽  
Arthur Andersen ◽  
Practical Implications

Purpose – This paper aims to, using evidence from a former office of the public accounting firm Arthur Andersen, to study the importance of the relational content and structure of individuals’ social connections as they transitioned to subsequent employment. The paper also examines the maintenance of their social networks through time. Implications for careers in the accounting field are offered. Practicing accountants’ connections with other individuals have often been recognized as an important resource that influences career success. However, these social networks have escaped systematic academic study in accounting. Design/methodology/approach – Social network analysis, built on survey data. Findings – The results show that who one was connected to in a previous employment was more important than one’s overall network position when deciding whether to stay or exit public accounting. However those who exited public accounting did not demonstrate a handicap in maintaining network structures after the disbanding of the firm. Research limitations/implications – This study is limited to firm members, and to a single office of a firm. Social network analysis was used as a research tool for the sociology of public accounting. Practical implications – Implications are for careers in public accounting, and the management of human resources in public accounting is offered. Social implications – The paper has implications for the successfulness of professional service provision in a general sense. Originality/value – Almost a decade of social connection is studied with a method that has not appeared in the discipline but is well regarded in management studies.

scholarly journals Using Social Network Analysis to Explore Digital Student Interactions and Business Competency Learning in a Web-based Educational Platform

2015 ◽  
Vol 6 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Andrew Feldstein ◽  
Kim Gower
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Web 2.0 ◽  
Learning Community ◽  
Student Behaviors ◽  
Global Business ◽  
Student Interactions ◽  
Web Based ◽  
Rich Data

Web 2.0 tools occupy a large part of our lives, and their use in the classroom offers instructors a unique opportunity to gather substantial information about individual and interactive student behaviors. The authors' challenge is understanding the implications of this rich data source for assessing course efficacy and student learning, and applying these insights to further enhance the development of global business competencies. This paper reviews 311 student interactions as reflected in comments exchanged in a digital social learning community and, using social network analysis, discusses the potential to use these interactions to assess student critical thinking, communication, and collaborative feedback skills. The authors conclude with implications and recommendations for instructors who want to use Web 2.0 platforms and data to enhance their understanding of student and class digital interactions, and apply this information to course enhancement.

The Sense of e-Learning Community Index (SeLCI) for Computer Supported Collaborative e-Learning (CSCeL)

2011 ◽  
pp. 672-698
Author(s):  
Niki Lambropoulos
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Learning Community ◽  
Social Engagement ◽  
Sense Of Belonging ◽  
Skills Acquisition ◽  
Online Teachers ◽  
Community Identification ◽  
E Learning

The aim of this research is to shed light in collaborative e-learning communities in order to observe, analyse and support the e-learning participants. The research context is the Greek teachers’ e-learning community, started in 2003 as part of a project for online teachers’ training and aimed at enabling teachers to acquire new competencies. However, these aims were not met because of passive participation; therefore this study aimed to enhance the Greek teachers’ social engagement to achieve the new skills acquisition. Therefore, the initial sense of community identification was based on empathy; however, because it was inadequate to fully describe the context,, a Sense of E-Learning Community Index (SeLCI) was developed. The new SeLCI attributes were: community evolution; sense of belonging; empathy; trust; intensity characterised by e-learners’ levels of participation and persistence on posting; collaborative e-learning quality measured by the quality in Computer Supported Collaborative eLearning (CSCeL) dialogical sequences, participants’ reflections on own learning; and social network analysis based on: global cohesion anchored in density, reciprocity, cliques and structural equivalence, global centrality derived from in- and out-degree centrality and closeness; and local nodes and centrality in real time. Forty Greek teachers participated in the study for 30 days using Moodle and enhanced Moodle with to measure participation, local Social network Analysis and critical thinking levels in CSCeL. Quantitative, qualitative, Social Network Analysis and measurements produced by the tools were used for data analysis. The findings indicated that each of the SeLCI is essential to enhance participation, collaboration, internalisation and externalisation of knowledge to ensure the e-learning quality and new skills acquisition. Affective factors in CSCeL (sense of belonging, empathy and trust) were also essential to increase reciprocity and promote active participation. Community management, e-learning activities and lastly, the technology appear to affect CSCeL.

Observing the Evolution of a Learning Community Using Social Network Analysis

2011 ◽  
pp. 215-231
Author(s):  
Francesca Grippa ◽  
Marco De Maggio ◽  
Angelo Corallo
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Community Development ◽  
Learning Communities ◽  
Learning Community ◽  
Learning Environments ◽  
Computer Scientists ◽  
Clear Identification ◽  
Network Metrics ◽  
Contribution Index

During the last decades, social and computer scientists have been focusing their efforts to study the effectiveness of collaboration in both working and learning environments. The main contributions clearly identify the importance of interactivity as the determinant of positive performances in learning communities where the supportive dimension of exchanges is balanced by the interactive one. In this chapter, authors describe a method based on social network metrics to recognize the stages of development of learning communities. The authors found that the evolution of social network metrics - such as density, betweenness centrality, contribution index, core/periphery structure – matched the formal stages of community development, with a clear identification of the forming, norming, and storming phases.

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