Emerging Forms of Collaboration

2016 ◽  
pp. 69-99
Author(s):  
Alexandra Antonopoulou ◽  
Eleanor Dare
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Of Practice ◽  
Motion Capture ◽  
Interaction Design ◽  
Collaborative Technologies ◽  
Custom Made ◽  
New Form

The chapter will outline the implications of two projects, namely the ‘Phi Books' (2008) and the ‘Digital Dreamhacker' (2011). These novel projects serve here as case studies for investigating new and challenging ways of advancing collaborative technologies, using in particular, Communities of Practice and insights gained from both embodiment and graph theory (social network analysis) as well as design. Both projects were developed collaboratively, between a computer programmer and a designer and a wider community of practice, consisting of other artists, writers, technologists and designers. The two systems that resulted also acted as methodologies, instigated by the authors with a view to facilitate, explore and comment on the act of collaboration. Both projects are multi-disciplinary, spanning ideas and techniques from mathematics and art, design and computer programming. The projects deploy custom-made software and fiction enmeshed structures, drawing upon methodologies that are embedded with dreams and stories while at the same time being informed by cutting-edge research into human behaviour and interaction design. The chapter will investigate how the projects deployed techniques and theoretical insights from social network analysis as well as motion capture technology and the wider concept of a Community of Practice, to extend and augment existing collaborative methods. The chapter draws upon Wenger et al (2002), as well as Siemens (2014) and Borgatti et al (2009), and will explore the idea of a new form of collective social and technological collaborative grammar, deploying gesture as well as Social Network Analysis. Moreover, the featured projects provide insights into the ways in which digital technology is changing society, and in turn, the important ways in which technology is embedded with the cultural and economic prerogatives of increasingly globalized cultures.

Understanding the Video Bloggers’ Community

2013 ◽  
pp. 63-79
Author(s):  
John Warmbrodt ◽  
Hong Sheng ◽  
Richard Hall ◽  
Jinwei Cao
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Business Applications ◽  
Shared Interest ◽  
New Form ◽  
The Rich

Video blogs (or vlogs) are a new form of blogs where each post is a video. This study explores a community of video bloggers (or vloggers) by studying the community’s structure as well as the motivations and interactions of vloggers in the community. A social network analysis of a list of personal vloggers identifies the community’s structure. Open-ended interviews with core vloggers in the sample provide in-depth understanding on the motivations and interactions of the vloggers. Overall, the results indicate that the vloggers’ community exhibits a core/periphery structure. Such a community is formed based on shared interest and active interactions. In addition, the rich communication provided in video blogs allows for a more personal and intimate interaction, making vlogs a potentially powerful tool for business applications.

scholarly journals Group Measures and Modeling for Social Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Vincent Levorato
Keyword(s):  
Complex System ◽  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Modeling ◽  
Complex Interactions ◽  
Social Network Modeling

Social network modeling is generally based on graph theory, which allows for study of dynamics and emerging phenomena. However, in terms of neighborhood, the graphs are not necessarily adapted to represent complex interactions, and the neighborhood of a group of vertices can be inferred from the neighborhoods of each vertex composing that group. In our study, we consider that a group has to be considered as a complex system where emerging phenomena can appear. In this paper, a formalism is proposed to resolve this problematic by modeling groups in social networks using pretopology as a generalization of the graph theory. After giving some definitions and examples of modeling, we show how some measures used in social network analysis (degree, betweenness, and closeness) can be also generalized to consider a group as a whole entity.

scholarly journals A Transnational Research Collaboration: A Social Network Analysis and Perspectives on Our Community of Practice

Quest ◽  
2021 ◽  
pp. 1-15
Author(s):  
Phillip Ward ◽  
Erhan Devrilmez ◽  
Shiri Ayvazo ◽  
Fatih Dervent ◽  
Yaohui He ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Of Practice ◽  
Research Collaboration

Discovering Communities of Practice Through Social Network Analysis

2011 ◽  
pp. 129-130
Author(s):  
Cindi Smatt ◽  
Molly McLure Wasko
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Communities Of Practice ◽  
Competitive Advantage ◽  
Community Of Practice ◽  
Knowledge Economy ◽  
Building Block ◽  
Autonomous Communities ◽  
Network Connections

The concept of a community of practice is emerging as an essential building block of the knowledge economy. Brown and Duguid (2001) argue that organizations should be conceptualized as consisting of autonomous communities whose interactions can foster innovation within an organization and accelerate the introduction of innovative ideas. The key to competitive advantage depends on a firm’s ability to coordinate across autonomous communities of practice internally and leverage the knowledge that flows into these communities from network connections (Brown & Duguid, 2001). But how does an organization do this? A key challenge for management is understanding how to balance strategies that capture knowledge without killing it (Brown & Duguid, 2000).

Structural Analysis With Graphs

2020 ◽  
pp. 31-47
Keyword(s):  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Structural Analysis ◽  
Network Analysis ◽  
Social Research ◽  
Analysis Methods

Graphs are mathematical formalisms that represent social networks very well. Analysis methods using graph theory have started to develop substantially along with the advancement of mathematics and computer sciences in recent years, with contributions from several disciplines including social network analysis. Learning how to use graphs to represent social networks is important not only for employing theoretical insights of this advanced field in social research, but also for the practical purposes of utilizing its mature and abundant tools. This chapter explores structural analysis with graphs.

scholarly journals Social Network Analysis and Churn Prediction in Telecommunications Using Graph Theory

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 753 ◽  
Author(s):  
Stefan M. Kostić ◽  
Mirjana I. Simić ◽  
Miroljub V. Kostić
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Churn Prediction ◽  
Network Graph ◽  
Network Analytics ◽  
Telecommunications Market ◽  
Market Saturation ◽  
Important Nodes

Due to telecommunications market saturation, it is very important for telco operators to always have fresh insights into their customer’s dynamics. In that regard, social network analytics and its application with graph theory can be very useful. In this paper we analyze a social network that is represented by a large telco network graph and perform clustering of its nodes by studying a broad set of metrics, e.g., node in/out degree, first and second order influence, eigenvector, authority and hub values. This paper demonstrates that it is possible to identify some important nodes in our social network (graph) that are vital regarding churn prediction. We show that if such a node leaves a monitored telco operator, customers that frequently interact with that specific node will be more prone to leave the monitored telco operator network as well; thus, by analyzing existing churn and previous call patterns, we proactively predict new customers that will probably churn. The churn prediction results are quantified by using top decile lift metrics. The proposed method is general enough to be readily adopted in any field where homophilic or friendship connections can be assumed as a potential churn driver.

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