Topics in social network analysis and network science

This chapter introduces statistical methods used in the analysis of social networks and in the rapidly evolving parallel-field of network science. Although several instances of social network analysis in health services research have appeared recently, the majority involve only the most basic methods and thus scratch the surface of what might be accomplished. Cutting-edge methods using relevant examples and illustrations in health services research are provided

NEW DIRECTIONS IN ONLINE COMMUNITY RESEARCH

Information Systems researchers have studied multiple forms of online communities for decades. Significant progress has been made in addressing research questions such as how and when individuals are motivated to contribute knowledge in online settings. Yet, not only are important questions unanswered—such as why online communities succeed or fail—but also there still remains disagreement on the basic definition of online community. Furthermore, as the diversity of users and uses of online media continues to increase, IS researchers can now ask and answer different questions. For example, advances in social computing, mobile computing, and social media support new forms of online communities. In this panel we will propose and debate the direction of an online community research agenda for the next decade and beyond

A survey of statistical network models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Comment: 96 pages, 14 figures, 333 reference

Stochastic Weighted Graphs: Flexible Model Specification and Simulation

In most domains of network analysis researchers consider networks that arise in nature with weighted edges. Such networks are routinely dichotomized in the interest of using available methods for statistical inference with networks. The generalized exponential random graph model (GERGM) is a recently proposed method used to simulate and model the edges of a weighted graph. The GERGM specifies a joint distribution for an exponential family of graphs with continuous-valued edge weights. However, current estimation algorithms for the GERGM only allow inference on a restricted family of model specifications. To address this issue, we develop a Metropolis--Hastings method that can be used to estimate any GERGM specification, thereby significantly extending the family of weighted graphs that can be modeled with the GERGM. We show that new flexible model specifications are capable of avoiding likelihood degeneracy and efficiently capturing network structure in applications where such models were not previously available. We demonstrate the utility of this new class of GERGMs through application to two real network data sets, and we further assess the effectiveness of our proposed methodology by simulating non-degenerate model specifications from the well-studied two-stars model. A working R version of the GERGM code is available in the supplement and will be incorporated in the gergm CRAN package.Comment: 33 pages, 6 figures. To appear in Social Network

Enterprise Social Networks – Contributions to Research with respect to Actor Roles in Knowledge Management, the Role of Formal Hierarchies, and Network Evolution

In recent years, a new class of information technologies, called social media, has soared in popularity, and increasingly becomes part of people’s daily lives. Although originally designed for private use, an increasing number of organisations have begun to adopt social media for organisational purposes (Kane 2015). ). However, social media in general and OSN in particular cannot only be used for marketing purposes. Indeed, they can be used by a company along the whole value chain (Chui et al. 2012). In addition, social media can help organisations to support communication and collaboration within the organisation and to “work more effectively across geographic and cultural boundaries” (Kane 2015, p. 1). Already in 2012, a study estimated the economic impact of social media, mostly gained from more efficient communication and collaboration between USD 900 billion and USD 1.3 trillion (Chui et al. 2012). However, publicly available social media services cannot support all needs of an organization. Thus, with enterprise social networks (ESN) a new class of social media services designed for internal use has emerged. In recent years, many organisations have started implementing ESN on the one hand to foster internal collaboration, communication, and knowledge-sharing (Aral et al. 2013; von Krogh 2012). Against this background, the two subject areas that this dissertation focuses on are of increasing interest to both research and practice: First, this dissertation addresses research on OSN (Subject A) as OSN are amongst the most popular and most widely used social media services. Thus, this leads to a steadily growing number of publications in most major outlets of the global information systems (IS) community (Richter et al. 2011). To assess the knowledge and the research fields that have been predominantly addressed by the IS community so far (Scandura and Williams 2000), this dissertation aims to provide a structured literature overview on the prior IS literature, including the recent developments in the field as well as fields that need to be addressed in further research. Here, five research fields that already have been addressed as well as ten research gaps are described and discussed. Second, this dissertation aims at adding to research on ESN (Subject B). As noted, the potential of ESN for knowledge management, has been noticed by organisations and led to an increasing demand to better understand their role in knowledge practices like information seeking, knowledge sharing or expert finding (Bharadwaj et al. 2013; Herzog et al. 2013; Richter et al. 2013In this line of argument, there is a need to investigate different actor roles in ESN usage (Trier and Richter 2015) to better understand the role and potential of ESN as well as their users’ behaviour (Koo et al. 2011). Next to identifying and characterising value adding users, two measures fort he classification of users based on their amount of sharing and seeking knowledge were proposed. Here, it could be shown that users who actively share their knowledge in the ESN have a central position in the network structure. Formal organisational hierarchy is an essential and pervasive organisational characteristic, which might influence the creation of social relations and communication in ESN. Practice-orientated contributions argue that ESN can lead to flatter organisational hierarchy in companies (McAfee 2009). However, it is still largely unanswered, whether and how formal organisational hierarchies influence users’ networking behaviour in ESN and if these effects inside the ESN differ from those in the work place outside the ESN. Within this dissertation the significant effects of formal hierarchies on interaction behaviour within the ESN could be shown. Nevertheless, they seem to be weaker inside the ESN and seem to decrease in time. Moreover, it has to be considered that the underlying networking structures are not static. Indeed, the structure of an ESN is highly dynamic as more and more users are participating and creating new relations to other users (Ghosh and Ganguly 2014). While the evolution of other social media networks already has been investigated (cf. e.g., Ghosh and Ganguly 2014; Kumar et al. 2010), scarce attention has been paid to the structure and evolution of ESN. Against this background this dissertation investigated how the structure of an ESN changes in time as well as what are drivers for the creation of new relationships between the users. Here, a significant correlation between network centrality and new social relationships was found

Sustainability at the Indigenous—West Boundary: The case of a boundary organization working with the Waorani of the Pastaza Province

abstract: The Woarani of the Pastaza Province in Amazonian Ecuador face complex pressures both externally and internally to develop. While there are both positive and negative impacts associated with this transition, it remains a problem that development solutions designed external to the system they’re meant to impact risk imposing asymmetries on that system. This research explores the case of a culturally and historically embedded boundary organization operating at the nexus between Western academics and two communities of Woarani in the Pastaza Province of Ecuador. Through unstructured and semi-structured interviews, field- observation and social and historical research, this study seeks to understand: 1) the pathways to development for the Waorani, what and why they choose what they do and, 2) in the context of the I-W boundary at the field school site, the elements of development that are critical for sustainable scaling. Key findings include eight elements that explain development at the field school and situate the school as a boundary organization. Another important finding is the support for sustainable scaling, that in this context, sustainable scaling is modeled by organic growth along known networks of relations

A Survey of Statistical Network Models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active “network community” and a substantial liter- ature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning net- work literature in statistical physics and computer science. The growthof the World Wide Web and the emergence of online “networking com- munities” such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize for- mal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Statistic

Indirect Reciprocity in Contributions to a Peer-to-Peer Music Sharing Network - An Empirical Analysis of Individual Level Data

This study assesses the influence of indirect reciprocity on individual contribution to a peer-to-peer network. We find that individuals’ level of contributions increases with number of contributors in the peer-to-peer network but decrease with number of free riders in the networks, indicating that individual contributions are reciprocal in nature. Moreover, we show that individuals have strong incentive to punish free riders and reward contributors in the peer-to-peer network. They do so through the setting of servers that allows discrimination among downloaders. When number of free riders increases, individuals are more likely to change the server settings to provide priority services to contributors and lesser services to free riders. The phenomena are consistent with findings from economic experiments which suggest that reciprocity and the ability to punish free riders could sustain contribution to pubic goods. The findings have important implications on the design and practical management of peer-to-peer networks

Public Innovation and Digital Transformation

Public innovation and digitalization are reshaping organizations and society in various ways and within multiple fields, as innovations are essential in transforming our world and addressing global sustainability and development challenges. This book addresses the fascinating relationship of these two contemporary topics and explores the role of digital transformation in promoting public innovation. This edited collection includes examples of innovations that emerge suddenly, practices for processing innovations, and the requirements for transformation from innovation to the ""new normal"". Acknowledging that public innovation refers to the development and realization of new and creative ideas that challenge conventional wisdom and disrupt the established practices within a specific context, expert contributions from international scholars explore and illustrate the various activities that are happening in the world of multiple digitalization opportunities. The content covers public administration, technical and business management, human, social, and future sciences, paying attention to the interaction between public and private sectors to utilize digitalization in order to facilitate public innovation. This timely book will be of interest to researchers, academics and students in the fields of technology and innovation management, as well as knowledge management, public service management and administration