From Logistic Networks to Social Networks


Book Description

As a result of its widespread implementation in economic and social structures, the network concept appears to be a paradigm of the contemporary world. The need for various services – transport, energy, consumption of manufacturing goods, provision of care, information and communication, etc. – draws users into interwoven networks which are meshes of material and immaterial flows. In this context, the user is a consumer of goods and services from industries and administrations, or they themselves are part of the organization (digital social networks). This book examines the invariants that unify networks in their diversity, as well as the specificities that differentiate them. It provides a reading grid that distinguishes a generic level where these systems find a common interpretation, and a specific level where appropriate analytical methods are used. Three case studies from different fields are presented to illustrate the purpose of the book in detail.




Virtual Communities, Social Networks and Collaboration


Book Description

Online communities are among the most obvious manifestations of social networks based on new media technology. Facilitating ad-hoc communication and leveraging collective intelligence by matching similar or related users have become important success factors in almost every successful business plan. Researchers are just beginning to understand virtual communities and collaborations among participants currently proliferating across the world. Virtual Communities, Social Networks and Collaboration covers cutting edge research topics of utmost real-world importance in the specific domain of social networks. This volume focuses on exploring issues relating to the design, development, and outcomes from electronic groups and online communities, including: - The implications of social networking, - Understanding of how and why knowledge is shared among participants, - What leads to participation, effective collaboration, co-creation and innovation, - How organizations can better utilize the potential benefits of communities in both internal operations, marketing, and new product development.




Social Network Analysis of Disaster Response, Recovery, and Adaptation


Book Description

Social Network Analysis of Disaster Response, Recovery, and Adaptation covers systematic social network analysis and how people and institutions function in disasters, after disasters, and the ways they adapt to hazard settings. As hazards become disasters, the opportunities and constraints for maintaining a safe and secure life and livelihood become too strained for many people. Anecdotally, and through many case studies, we know that social interactions exacerbate or mitigate those strains, necessitating a concerted, intellectual effort to understand the variation in how ties within, and outside, communities respond and are affected by hazards and disasters. - Examines the role of societal relationships in a disaster context, incorporating theory and case studies by experts in the field - Integrates research in the areas of social network analysis and inter-organizational networks - Presents a range of studies from around the world, employing different approaches to network analysis in disaster contexts




From Sociology to Computing in Social Networks


Book Description

Important aspects of social networking analysis are covered in this work by combining experimental and theoretical research. A specific focus is devoted to emerging trends and the industry needs associated with utilizing data mining techniques. Some of the techniques covered include data mining advances in the discovery and analysis of communities, in the personalization of solitary activities (like searches) and social activities (like discovering potential friends), in the analysis of user behavior in open fora (like conventional sites, blogs and fora) and in commercial platforms (like e-auctions), and in the associated security and privacy-preservation challenges; as well as social network modeling, scalable, customizable social network infrastructure construction, and the identification and discovery of dynamic growth and evolution patterns using machine learning approaches or multi-agent based simulation. These topics will be of interest to practitioners and researchers alike in this dynamic and growing field.




Prediction and Inference from Social Networks and Social Media


Book Description

This book addresses the challenges of social network and social media analysis in terms of prediction and inference. The chapters collected here tackle these issues by proposing new analysis methods and by examining mining methods for the vast amount of social content produced. Social Networks (SNs) have become an integral part of our lives; they are used for leisure, business, government, medical, educational purposes and have attracted billions of users. The challenges that stem from this wide adoption of SNs are vast. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection. This text has applications to widely used platforms such as Twitter and Facebook and appeals to students, researchers, and professionals in the field.




The SAGE Handbook of Social Network Analysis


Book Description

This sparkling Handbook offers an unrivalled resource for those engaged in the cutting edge field of social network analysis. Systematically, it introduces readers to the key concepts, substantive topics, central methods and prime debates. Among the specific areas covered are: Network theory Interdisciplinary applications Online networks Corporate networks Lobbying networks Deviant networks Measuring devices Key Methodologies Software applications. The result is a peerless resource for teachers and students which offers a critical survey of the origins, basic issues and major debates. The Handbook provides a one-stop guide that will be used by readers for decades to come.




Successfully managing challenges in German-Chinese logistics networks


Book Description

The present study has been developed by the Kuehne Competence Center for International Logistics Networks at the Department of Logistics, Technische Universität Berlin, Germany. It is a report on intermediate results of a project funded by the Kuehne Foundation, Switzerland and conducted in cooperation with the Chair of International Logistics Networks and Services at the Tongji University, Shanghai, China. The study presents results from several years of work looking into successful Western firms’ operations in the Chinese market. It lists current and emerging logistical challenges in German-Chinese logistics networks and proposes a set of mitigation strategies. The study also gives in-depth insights into three case studies from the automotive, electronics and consumer goods industries. The China-specific nature of this study is exemplary for many culturally distinct bilateral trade relationships around the world. The entire study is enriched with up-to-date macro- and micro-economic data, as well as a study of seminal literature in the field; applied research methodologies include two group exercises with forty-two practitioners, several online questionnaires with over fifty respondents and three in-depth case studies. Die vorliegende Studie wurde vom Kompetenzzentrum für Internationale Logistiknetze am Fachgebiet Logistik der Technischen Universität Berlin, Deutschland, erstellt. Sie enthält die bisherigen Projektergebnisse eine Forschungsprojekts, welches von der Kühne-Stiftung, Schweiz gefördert und in Kooperation mit der Tongi Universität Shanghai, China durchgeführt wird. Die Studie präsentiert die Ergebnisse einer langjährigen Analyse erfolgreicher westlicher Unternehmen im chinesischen Markt. Sie stellt aktuelle und zukünftige logistische Herausforderungen in Deutsch-Chinesischen Logistiknetzen dar und erarbeitet Gegenmaßnahmen. Die Studie bietet außerdem Einblick in drei umfangreiche Fallstudien aus der Automotive-, Elektronik- und Konsumgüterindustrie. Der Fokus auf den Chinesischen Markt ist hierbei exemplarisch für viele kulturell unterschiedliche Geschäftsbeziehungen in internationalen Netzen. Die Studie enthält zudem aktuelle mikro- und makroökonomische Daten, sowie eine Analyse relevanter Literatur. Es werden verschiedene wissenschafliche Methoden angewand, dazu gehören Gruppenarbeiten mit 42 Praktikern, mehere Onlineumfragen und drei umfangreiche Fallstudien.




Social Network Analysis


Book Description

David Knoke and Song Yang's Social Network Analysis, Third Edition provides a concise introduction to the concepts and tools of social network analysis. The authors convey key material while at the same time minimizing technical complexities. The examples are simple: sets of 5 or 6 entities such as individuals, positions in a hierarchy, political offices, and nation-states, and the relations between them include friendship, communication, supervision, donations, and trade. The new edition reflects developments and changes in practice over the past decade. The authors also describe important recent developments in network analysis, especially in the fifth chapter. Exponential random graph models (ERGMs) are a prime example: when the second edition was published, P* models were the recommended approach for this, but they have been replaced by ERGMs. Finally, throughout the volume, the authors comment on the challenges and opportunities offered by internet and social media data.




Longitudinal Network Models


Book Description

Although longitudinal social network data are increasingly collected, there are few guides on how to navigate the range of available tools for longitudinal network analysis. The applied social scientist is left to wonder: Which model is most appropriate for my data? How should I get started with this modeling strategy? And how do I know if my model is any good? This book answers these questions. Author Scott Duxbury assumes that the reader is familiar with network measurement, description, and notation, and is versed in regression analysis, but is likely unfamiliar with statistical network methods. The goal of the book is to guide readers towards choosing, applying, assessing, and interpreting a longitudinal network model, and each chapter is organized with a specific data structure or research question in mind. A companion website includes data and R code to replicate the examples in the book.




Social Network Analysis


Book Description

SOCIAL NETWORK ANALYSIS As social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose. Social network analysis is the solicitation of network science on social networks, and social occurrences are denoted and premeditated by data on coinciding pairs as the entities of opinion. The book features: Social network analysis from a computational perspective using python to show the significance of fundamental facets of network theory and the various metrics used to measure the social network. An understanding of network analysis and motivations to model phenomena as networks. Real-world networks established with human-related data frequently display social properties, i.e., patterns in the graph from which human behavioral patterns can be analyzed and extracted. Exemplifies information cascades that spread through an underlying social network to achieve widespread adoption. Network analysis that offers an appreciation method to health systems and services to illustrate, diagnose, and analyze networks in health systems. The social web has developed a significant social and interactive data source that pays exceptional attention to social science and humanities research. The benefits of artificial intelligence enable social media platforms to meet an increasing number of users and yield the biggest marketplace, thus helping social networking analysis distribute better customer understanding and aiding marketers to target the right customers. Audience The book will interest computer scientists, AI researchers, IT and software engineers, mathematicians.