Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks. Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form. The book explores critical elements of network analysis in detail, including the measurement of distance and centrality, the detection of communities and cliques, and the analysis of assortativity and similarity. An extension chapter offers an introduction to graph database technologies. Real data sets from various research contexts are used for both instruction and for end of chapter practice exercises and a final chapter contains data sets and exercises ideal for larger personal or group projects of varying difficulty level. Key features: Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.

Graphs are about connections, and are an important part of our connected and data-driven world. A Librarian's Guide to Graphs, Data and the Semantic Web is geared toward library and information science professionals, including librarians, software developers and information systems architects who want to understand the fundamentals of graph theory, how it is used to represent and explore data, and how it relates to the semantic web. This title provides a firm grounding in the field at a level suitable for a broad audience, with an emphasis on open source solutions and what problems these tools solve at a conceptual level, with minimal emphasis on algorithms or mathematics. The text will also be of special interest to data science librarians and data professionals, since it introduces many graph theory concepts by exploring data-driven networks from various scientific disciplines. The first two chapters consider graphs in theory and the science of networks, before the following chapters cover networks in various disciplines. Remaining chapters move on to library networks, graph tools, graph analysis libraries, information problems and network solutions, and semantic graphs and the semantic web. - Provides an accessible introduction to network science that is suitable for a broad audience - Devotes several chapters to a survey of how graph theory has been used in a number of scientific data-driven disciplines - Explores how graph theory could aid library and information scientists

Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.

This two-volume encyclopedia provides a thorough introduction to the wide-ranging, fast-developing field of social networking, a much-needed resource at a time when new social networks or "communities" seem to spring up on the internet every day. Social networks, or groupings of individuals tied by one or more specific types of interests or interdependencies ranging from likes and dislikes, or disease transmission to the "old boy" network or overlapping circles of friends, have been in existence for longer than services such as Facebook or YouTube; analysis of these networks emphasizes the relationships within the network . This reference resource offers comprehensive coverage of the theory and research within the social sciences that has sprung from the analysis of such groupings, with accompanying definitions, measures, and research. Featuring approximately 350 signed entries, along with approximately 40 media clips, organized alphabetically and offering cross-references and suggestions for further readings, this encyclopedia opens with a thematic Reader′s Guide in the front that groups related entries by topics. A Chronology offers the reader historical perspective on the study of social networks. This two-volume reference work is a must-have resource for libraries serving researchers interested in the various fields related to social networks.

How can HR practitioners with little or no experience of analytics feel confident in their ability to find, analyse and use workforce data to make better business decisions? This book has the answers. An understanding of people analytics is a crucial skill for all HR professionals. This new edition provides expert guidance on the key aspects of analytics, enabling all HR professionals to feel confident in their ability to handle employee and organizational data. It features new material on applying data to respond to external disruption such as COVID-19 as well as how to develop a people analytics journey. There is also advice on recruiting people analytics specialists and embedding new data-driven operating models within HR. This book is essential reading for all HR professionals to develop understanding of how and where HR analytics can make a tangible difference to organizations. With updated case studies and thought leadership examples from companies including NHS, AstraZeneca and Swarovski, this book demonstrates how people analytics can be leveraged to improve culture and employee engagement, increase performance and reduce costs.

Modern businesses depend on data for their very survival, creating a need for sophisticated databases and database technologies to help store, organise and transport their valuable data. This updated and expanded, easy-to-read textbook/reference presents a comprehensive introduction to databases, opening with a concise history of databases and of data as an organisational asset. As relational database management systems are no longer the only database solution, the book takes a wider view of database technology, encompassing big data, NoSQL, object and object-relational, and in-memory databases. Presenting both theoretical and practical elements, the new edition also examines the issues of scalability, availability, performance and security encountered when building and running a database in the real world. Topics and features: Presents review and discussion questions at the end of each chapter, in addition to skill-building, hands-on exercises Provides new material on database adaptiveness, integration, and efficiency in relation to data growth Introduces a range of commercial databases and encourages the reader to experiment with these in an associated learning environment Reviews use of a variety of databases in business environments, including numerous examples Discusses areas for further research within this fast-moving domain With its learning-by-doing approach, supported by both theoretical and practical examples, this clearly-structured textbook will be of great value to advanced undergraduate and postgraduate students of computer science, software engineering, and information technology. Practising database professionals and application developers will also find the book an ideal reference that addresses today's business needs.

The Oxford Handbook of Social Networks gathers forty leading scholars in social networks who link the distinct practices of social network scholars in the social sciences. Each chapter provides a succinct background to, and future directions for, distinctive approaches to analyzing social networks--theoretical, methodological, or substantive. The Handbook serves as a resource for graduate students and faculty new to networks looking to learn new approaches, scholars interested in an overview of the field, and network analysts looking to expand their skills or substantive areas of research.

"This book discusses the new technologies of semantic Web, transforming the way we use information and knowledge"--Provided by publisher.