Social Network Theory and Analysis: A Complementary Lens for Inquiry

ObjectivesSocial network analysis focuses on the relationships between people and structures that form through their interactions. Research in the field has shown that people can be influenced by their social...

ObjectivesSocial network analysis focuses on the relationships between people and structures that form through their interactions. Research in the field has shown that people can be influenced by their social...

The seventh SNA-KDD workshop is proposed as the seventh in a successful series of workshops on social network mining and analysis co-held with KDD, soliciting experimental and theoretical work on social network mining and analysis in both online and offline social network systems. In recent years, social network research has advanced significantly, thanks to the prevalence of the online social websites and instant messaging systems as well as the availability of a variety of large-scale offline social network systems. These social network systems are usually characterized by the complex network structures and rich accompanying contextual information. Researchers are increasingly interested in addressing a wide range of challenges residing in these disparate social network systems, including identifying common static topological properties and dynamic properties during the formation and evolution of these social networks, and how contextual information can help in analyzing the pertaining social networks. These issues have important implications on community discovery, anomaly detection, trend prediction and can enhance applications in multiple domains such as information retrieval, recommendation systems, security and so on. The past SNA-KDD workshops have achieved significant attentions from the world-wide researchers working in different aspects of social network analysis, including knowledge discovery and data mining in social network, social network modeling, multi-agent based social network simulation, complex generic network analysis and other related studies that can bring inspirations or be directly applied to social network analysis. Each year we received more than 30 submissions. The average acceptance rate is around 1/3.

Social network research hotspots and trends in public health: A bibliometric and visual analysis

Through an exhaustive review of the literature, this article looks at the applicability of social network analysis (SNA) in the field of humanresource development. The literature review revealed that a number of disciplines have adopted this unique methodology, which has assisted in the development of theory. SNA is a methodology for examining the structure among actors, groups, and organizations and aides in explaining variations in beliefs, behaviors, and outcomes. The article is divided into three main sections: social network theory and analysis, the social network approach and application to HRD. First, the article provides an overview of social network theory and SNA. Second, the process for conducting an SNA is described and third, the application of SNA to the field of HRD is presented. It is proposed that SNA can improve the empirical rigor of HRD theory building in such areas as organizational development, organizational learning, leadership development, organizational change, and training and development.

Chapter 3 - Privacy-Preserving Social Network Integration, Analysis, and Mining

This article aims toward developing a critical theory that can further advance feminist research in sport management. I seek to offer a critical analysis of gender relations in sport and leisure management by developing a theoretical critique of gender (in)equity that integrates both social theory and cultural analyses. The original empirical data was gathered in a national study of Gender Equity in Leisure Management conducted by the author in 1998/99 and secondary data was drawn from comparative studies undertaken in Australia, New Zealand, Canada, and the U.S. (Aitchison, Brackenridge, & Jordan, 1999; Henderson & Bialeschki, 1993, 1995; Mckay, 1996; Shinew & Arnold, 1998). The research cited demonstrates that women’s experience of sport and leisure management is shaped by both structural and cultural factors. My findings highlight the need for new epistemological perspectives as much as new methodological approaches and techniques. This new perspective acknowledges the complexities of gender–power relations in the workplace and recognizes the interconnectedness and mutually informing nature of structural and cultural power, thus opening the way for more sophisticated analyses and understandings of gender equity in sport and leisure management.

The rapid growth in popularity of online social networks provides new opportunities in computer science, sociology, math, information studies, biology, business, and more. Social network analysis (SNA) is a paramount technique supporting understanding social relationships and networks. Accordingly, certain studies and reviews have been presented focusing on information dissemination, influence analysis, link prediction, and more. However, the ultimate aim is for social network background knowledge and analysis to solve real-world social network problems. SNA still has several research challenges in this context, including users’ privacy in online social networks. Inspired by these facts, we have presented a survey on social network analysis techniques, visualization, structure, privacy, and applications. This detailed study has started with the basics of network representation, structure, and measures. Our primary focus is on SNA applications with state-of-the-art techniques. We further provide a comparative analysis of recent developments on SNA problems in the sequel. The privacy preservation with SNA is also surveyed. In the end, research challenges and future directions are discussed to suggest to researchers a starting point for their research.

Chapter 3 - Social Network Analysis: Measuring, Mapping, and Modeling Collections of Connections

Modeling, analysis, control, and management of complex social networks represent an important area of interdisciplinary research in an advanced digitalized world. In the last decade social networks have produced significant online applications which are running on top of a modern Internet infrastructure and have been identified as major driver of the fast growing Internet traffic. The "Second International Workshop on Modeling, Analysis and Management of Social Networks and Their Applications" (SOCNET 2018) held at Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany, on February 28, 2018, has covered related research issues of social networks in modern information society. The Proceedings of SOCNET 2018 highlight the topics of a tutorial on "Network Analysis in Python" complementing the workshop program, present an invited talk "From the Age of Emperors to the Age of Empathy", and summarize the contributions of eight reviewed papers. The covered topics ranged from theoretical oriented studies focusing on the structural inference of topic networks, the modeling of group dynamics, and the analysis of emergency response networks to the application areas of social networks such as social media used in organizations or social network applications and their impact on modern information society. The Proceedings of SOCNET 2018 may stimulate the readers' future research on monitoring, modeling, and analysis of social networks and encourage their development efforts regarding social network applications of the next generation.

The social network paradigm and applications in pharmacy

PurposeThe purpose of this paper is to provide examples of evaluating value‐creating networks and to address the organizational issues and challenges of a network orientation.Design/methodology/approachValue network analysis was first developed in 1993 and was adapted in 1997 for intangible asset management. It has been applied from shopfloor work groups to business webs and economic regions. It draws from a theory base of living systems, knowledge management, complexity theory, and intangible asset management.FindingsThe paper provides an overview of a value network analysis method and examples and insights from its practical application.Research limitations/implicationsThe paper does not provide a detailed comparative analysis with social network analysis, but rather looks forward to where interest in social networks may evolve into continuing concentration on value‐creating networks.Practical implicationsValue network analysis provides an opportunity to overcome the “split” in business management practices, where human interactions and relationships reside in one world of models and practices, and business processes and transactions reside in another. The engineering approaches of the last two decades have focused on driving out variation, with the unanticipated consequence of stifling organizational agility and innovation. The more human‐centric orientation of the value network perspective brings these two worlds together in a powerful, simple, and pragmatic way to model business activities.Originality/valueThe paper augments and expands the growing application of social or organizational network analysis by pointing to a next generation of analysis and analytics that can support organizational effectiveness. The value network analysis method fills a gap between network theory and practical application for managers, executives, analysts, and researchers.

Welcome to the Sixth IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial 2022). This year the workshop highlights novel algorithms and models that leverage parallel computing with applications in social network and social media analysis. The first set of papers focus on the key individual identification problem in social network analysis. The paper by Vandromme et al entitled “Efficient Parallel PageRank Algorithm for Network Analysis” proposes a more efficient parallel algorithm for PageRank that has been shown to improve the time complexity by a factor of two. In a similar vein, the paper by Sahu et al entitled “Dynamic Batch Parallel Algorithms for Updating PageRank” proposes two parallel algorithms for recomputing PageRank of nodes in a dynamic social network that can scale across various architectures. A related research problem is identifying opinion leaders that can improve information dissemination within communities. The paper entitled “Effect of Community-based Opinion Leaders on Guideline Dissemination in Large-Scale Physician Networks” by Murugappan et al, focuses on the problem of the dissemination of medical guidelines. The authors propose a culturally infused agent based model to analyze the effectiveness of various opinion leader selection strategies and the tradeoffs between the reach and rate of spread of medical guideline information. The next set of papers focus on social media analysis. Systems for large scale ingestion of social media data sets can support a wide range of research problems in computational social systems. A step in this direction is taken by authors Huber et al, who have proposed a parallel system for large scale processing of Reddit data in their paper entitled “A Streaming System for Large-scale Mining of Reddit Data”. On the other hand, authors Abeysinghe et al in their short research paper entitled “Unsupervised User Stance Detection on Tweets Against Web Articles Using Sentence Transformers”, have proposed a parallel computing based technique to identify the stance of users using the information and articles shared in their tweets. Finally, the short research paper by Bogle et al entitled “Distributed Algorithms for the Graph Biconnectivity and Least Common Ancestor Problems” focuses on the problem of connectivity in social networks and tackles the problem of identification of cut vertices and edges in networks by formulating a parallel biconnectivity algorithm for distributed graph structures.

Candidate change agent identification among men at risk for HIV infection

Good qualitative can help sport management researchers and industry professionals solve difficult problems and better understand their organisations, stakeholders and performance. Now in a fully revised and extended new edition, this book is a user-friendly introduction to qualitative methods in sport management. Covering the full process from planning to reporting results, this edition includes expanded coverage of cutting-edge areas including digital and social media research, critical realism, and social network analysis. The book examines the reflective and interrogative processes required for developing effective qualitative questions and includes a deeper discussion of ontology and epistemology in the light of today’s rapidly changing society. It takes the reader step-by-step through essential and emerging qualitative methods, from actor network theory and ethnography to computer-assisted data analysis and sampling typologies. Every chapter includes examples of real qualitative research, including shorter research briefs and extended case studies, reflecting the exciting qualitative that is currently occurring in sport business and management, and highlighting the links between and sport management practice. This is essential reading for courses in sport management, sport business, sport policy, sport marketing, sport media, and communications. It provides students, researchers, and practitioners with the knowledge and skills to undertake qualitative while deepening their understanding of how the social world can be perceived and interpreted through a particular theoretical lens. Useful online materials include recommended readings and PowerPoint slides.