Stephen P Borgatti – författare

Kickstart your research with this practical, bestselling guide to doing social network analysis. Get to grips with the mathematical foundations and learn how to use software tools such as NeTDraw and UCINET to reach your research goals.  Supporting you step-by-step through the entire research process, from design and data collection to coding, visualisation, and analysis, the book also offers: • Case studies and examples using real data  • Exercises drawn from the authors’ decades of teaching experience  • Online access to datasets, worked examples and a software manual to help you practice your skills. Whether you are new to social network analysis or an experienced researcher, this approachable book is your technical toolbox and research companion all in one. 

Social Networks at Work provides the latest thinking, from top-notch experts, on social networks as they apply to industrial and organizational (I/O) psychology. Each chapter provides an in-depth review along with discussions of future research and managerial implications of the social network perspective. Altogether, the volume illustrates the importance of adding a social capital perspective to the traditional human capital focus of I/O psychology.

The volume is organized into two groups of chapters: the first seven chapters focus on specific network concepts (such as centrality, affect, negative ties, multiplexity, cognition, and structural holes) applied across a variety of topics. The remaining eight chapters focus on common I/O topics (such as personality, creativity, turnover, careers, person–environment fit, employment, teams, and leadership) and examine each from a network perspective, applying a variety of network concepts to the topic.

This volume is suited for students and academics interested in applying a social network perspective to their work, as well as for practicing managers. Each topic area provides a useful review and guide for future research, as well as implications for managerial action.

Social Networks at Work provides the latest thinking, from top-notch experts, on social networks as they apply to industrial and organizational (I/O) psychology. Each chapter provides an in-depth review along with discussions of future research and managerial implications of the social network perspective. Altogether, the volume illustrates the importance of adding a social capital perspective to the traditional human capital focus of I/O psychology.

The volume is organized into two groups of chapters: the first seven chapters focus on specific network concepts (such as centrality, affect, negative ties, multiplexity, cognition, and structural holes) applied across a variety of topics. The remaining eight chapters focus on common I/O topics (such as personality, creativity, turnover, careers, person–environment fit, employment, teams, and leadership) and examine each from a network perspective, applying a variety of network concepts to the topic.

This volume is suited for students and academics interested in applying a social network perspective to their work, as well as for practicing managers. Each topic area provides a useful review and guide for future research, as well as implications for managerial action.

Kickstart your research with this practical, bestselling guide to doing social network analysis. Get to grips with the mathematical foundations and learn how to use software tools such as NeTDraw and UCINET to reach your research goals.  Supporting you step-by-step through the entire research process, from design and data collection to coding, visualisation, and analysis, the book also offers: • Case studies and examples using real data  • Exercises drawn from the authors’ decades of teaching experience  • Online access to datasets, worked examples and a software manual to help you practice your skills. Whether you are new to social network analysis or an experienced researcher, this approachable book is your technical toolbox and research companion all in one. 

Kickstart your research with this practical, bestselling guide to doing social network analysis. Get to grips with the mathematical foundations and learn how to use software tools such as NeTDraw and UCINET to reach your research goals.  Supporting you step-by-step through the entire research process, from design and data collection to coding, visualisation, and analysis, the book also offers: • Case studies and examples using real data  • Exercises drawn from the authors’ decades of teaching experience  • Online access to datasets, worked examples and a software manual to help you practice your skills. Whether you are new to social network analysis or an experienced researcher, this approachable book is your technical toolbox and research companion all in one. 

Kickstart your research with this practical, bestselling guide to doing social network analysis. Get to grips with the mathematical foundations and learn how to use software tools such as NeTDraw and UCINET to reach your research goals.  Supporting you step-by-step through the entire research process, from design and data collection to coding, visualisation, and analysis, the book also offers: • Case studies and examples using real data  • Exercises drawn from the authors’ decades of teaching experience  • Online access to datasets, worked examples and a software manual to help you practice your skills. Whether you are new to social network analysis or an experienced researcher, this approachable book is your technical toolbox and research companion all in one. 

This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it: • Discusses measures and techniques for analyzing social network data, including digital media  • Explains a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks • Offers digital resources like practice datasets and worked examples that help you get to grips with R software

This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it: • Discusses measures and techniques for analyzing social network data, including digital media  • Explains a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks • Offers digital resources like practice datasets and worked examples that help you get to grips with R software

This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it: • Discusses measures and techniques for analyzing social network data, including digital media  • Explains a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks • Offers digital resources like practice datasets and worked examples that help you get to grips with R software

This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it: • Discusses measures and techniques for analyzing social network data, including digital media  • Explains a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks • Offers digital resources like practice datasets and worked examples that help you get to grips with R software