John McLevey is an Associate Professor in the Department of Knowledge Integration at the University of Waterloo (ON, Canada). He is also appointed to the Departments of Sociology & Legal Studies and Geography and Environmental Management, is a Policy Fellow at the Balsillie School of International Affairs, and a Member of the Cybersecurity and Privacy Institute at the University of Waterloo. His work is funded by research grants from the Social Science and Humanities Research Council of Canada (SSHRC) and an Early Researcher Award from the Ontario Ministry of Research and Innovation. His current research project focuses on disinformation, censorship, and political deliberation in the public sphere across a wide variety of national contexts and political regimes. He wrote Doing Computational Social Science (SAGE Publishing, 2021) from his experiences as a researcher and advisor, as well as teaching courses in computational social science, data science, and research methods to students from diverse disciplinary backgrounds at the undergraduate and graduate level. John Scott is an Honorary Professor at the Universities of Essex, Exeter, and Copenhagen. He was formerly a professor of sociology at the Universities of Essex and Leicester, and pro-vice-chancellor for research at the University of Plymouth. He has been president of the British Sociological Association, Chair of the Sociology Section of the British Academy, and in 2013 was awarded the CBE for Services to Social Science. His work covers theoretical sociology, the history of sociology, elites and social stratification, and social network analysis. His most recent books include British Social Theory: Recovering Lost Traditions before 1950 (SAGE, 2018), Envisioning Sociology. Victor Branford, Patrick Geddes, and the Quest for Social Reconstruction (with Ray Bromley, SUNY Press, 2013), Objectivity and Subjectivity in Social Research (with Gayle Letherby and Malcolm Williams, SAGE, 2011).

• Chapter 1: Introduction - John Scott, John McLevey, and Peter J. CarringtonPart 1Chapter 2: Introducing Social Network Analysis - Christina Prell and David R. SchaeferChapter 3: Social Networks and Social Categories - Ronald Breiger and Robin Wagner-PacificiChapter 4: Social Networks and Computational Social Science - James A. Kitts, Helene Grogan and Kevin LewisChapter 5: Relational Sociology: Networks, Culture, and Interaction - Jan Fuhse and Ann MischePart 2Chapter 6: Social-ecological networks: What are they, why are they useful, and how can I use them? - Örjan BodinChapter 7: The Evolution of Environmental Policy Network Analysis - Tyler A. Scott, Mark Lubell and Gwen Arnold UC DavisChapter 8: Health Behaviors and Outcomes - Kayla de la HayeChapter 9: Political and policy networks - Mario DianiChapter 10: Social Movements and Collective Action - David TindallChapter 11: Gender and social networks - Elisa BellottiChapter 12: Why can’t we be friends? Understanding ethnic relations through network analysis - Rochelle CôtéChapter 13: Culture and Networks - Omar LizardoChapter 14: Semantic and Cultural Networks - Sarah Shugars and Sandra González-BailónChapter 15: Cognition and Social Networks - Matthew E. Brashears and Victoria MoneyChapter 16: Scientific Networks - Donghyun Kang and James EvansChapter 17: Crime and Networks - Marie Ouellet and Logan LedfordChapter 18: Historical Network Analysis: Two Problems of Scale - Ian KumekawaChapter 19: The Paradox of Behavior Change and the Science of Network Diffusion - Damon CentolaChapter 20: Network Interventions: Using Social Networks to Accelerate Diffusion of Innovations - Thomas W. ValenteChapter 21: Social Media and Digital Networks - Anabel Quan-Haase, Lyndsay Foisey and Riley McLaughlinChapter 22: Social Capital - Beate VölkerChapter 23: Social Support - Lijun Song and Zhe ZhangChapter 24: Corporate Networks - William K. Carroll, Jouke Huijzer and J. P. SapinskiChapter 25: International Trade Networks - Christina Prell, James Hollway, Petr Matous and Yasuyuki TodoPart 3Chapter 26: Centrality - M G Everett and S P BorgattiChapter 27: Structural Cohesion & Cohesive Groups - James Moody and Peter J. Mucha.Chapter 28: Multimodal social network analysis - Lorien JasnyChapter 29: Blockmodeling, Positions and Roles - Patrick Doreian, Anuška Ferligoj, and Vladimir BatageljChapter 30: Inferential Network Clustering with Hierarchical Bayesian Stochastic Blockmodels - Pierson Browne, Tyler Crick, and John McLeveyChapter 31: Personal Networks and Egocentric Analysis - Brea Perry, Adam Roth, and Mario SmallChapter 32: Multilevel Network Analysis - Emmanuel Lazega and Peng WangChapter 33:Exponential Random Graph Models - Johan KoskinenChapter 34: Network Dynamics - Tom A.B. Snijders and Christian E.G. SteglichChapter 35: Relational Event Models - Aaron Schecter and Noshir ContractorChapter 36: Latent Position Network Models - Hardeep Kaur, Riccardo Rastelli, Nial Friel and Adrian E. RafteryChapter 37: Negative Ties and Signed Networks - Filip AgneessensChapter 38: Qualitative and Mixed Methods - Betina HollsteinChapter 39: Spatial analysis of social networks - John R. HippChapter 40: Social Network Data Collection: Principles and Modalities - Jimi Adams and Miranda LubbersChapter 41: Missing Network Data - Robert W. Krause and Mark HuismanChapter 42: Scientific Software for Network Analysis - Pierson Browne, Adam Howe, Yasmin Koop-Monteiro, Yixi Yang, and John McLevey

John McLevey is an Associate Professor in the Department of Knowledge Integration at the University of Waterloo (ON, Canada). He is also appointed to the Departments of Sociology & Legal Studies and Geography and Environmental Management, is a Policy Fellow at the Balsillie School of International Affairs, and a Member of the Cybersecurity and Privacy Institute at the University of Waterloo. His work is funded by research grants from the Social Science and Humanities Research Council of Canada (SSHRC) and an Early Researcher Award from the Ontario Ministry of Research and Innovation. His current research project focuses on disinformation, censorship, and political deliberation in the public sphere across a wide variety of national contexts and political regimes. He wrote Doing Computational Social Science (SAGE Publishing, 2021) from his experiences as a researcher and advisor, as well as teaching courses in computational social science, data science, and research methods to students from diverse disciplinary backgrounds at the undergraduate and graduate level. John Scott is an Honorary Professor at the Universities of Essex, Exeter, and Copenhagen. He was formerly a professor of sociology at the Universities of Essex and Leicester, and pro-vice-chancellor for research at the University of Plymouth. He has been president of the British Sociological Association, Chair of the Sociology Section of the British Academy, and in 2013 was awarded the CBE for Services to Social Science. His work covers theoretical sociology, the history of sociology, elites and social stratification, and social network analysis. His most recent books include British Social Theory: Recovering Lost Traditions before 1950 (SAGE, 2018), Envisioning Sociology. Victor Branford, Patrick Geddes, and the Quest for Social Reconstruction (with Ray Bromley, SUNY Press, 2013), Objectivity and Subjectivity in Social Research (with Gayle Letherby and Malcolm Williams, SAGE, 2011).

• Chapter 1: Introduction - John Scott, John McLevey, and Peter J. CarringtonPart 1Chapter 2: Introducing Social Network Analysis - Christina Prell and David R. SchaeferChapter 3: Social Networks and Social Categories - Ronald Breiger and Robin Wagner-PacificiChapter 4: Social Networks and Computational Social Science - James A. Kitts, Helene Grogan and Kevin LewisChapter 5: Relational Sociology: Networks, Culture, and Interaction - Jan Fuhse and Ann MischePart 2Chapter 6: Social-ecological networks: What are they, why are they useful, and how can I use them? - Örjan BodinChapter 7: The Evolution of Environmental Policy Network Analysis - Tyler A. Scott, Mark Lubell and Gwen Arnold UC DavisChapter 8: Health Behaviors and Outcomes - Kayla de la HayeChapter 9: Political and policy networks - Mario DianiChapter 10: Social Movements and Collective Action - David TindallChapter 11: Gender and social networks - Elisa BellottiChapter 12: Why can’t we be friends? Understanding ethnic relations through network analysis - Rochelle CôtéChapter 13: Culture and Networks - Omar LizardoChapter 14: Semantic and Cultural Networks - Sarah Shugars and Sandra González-BailónChapter 15: Cognition and Social Networks - Matthew E. Brashears and Victoria MoneyChapter 16: Scientific Networks - Donghyun Kang and James EvansChapter 17: Crime and Networks - Marie Ouellet and Logan LedfordChapter 18: Historical Network Analysis: Two Problems of Scale - Ian KumekawaChapter 19: The Paradox of Behavior Change and the Science of Network Diffusion - Damon CentolaChapter 20: Network Interventions: Using Social Networks to Accelerate Diffusion of Innovations - Thomas W. ValenteChapter 21: Social Media and Digital Networks - Anabel Quan-Haase, Lyndsay Foisey and Riley McLaughlinChapter 22: Social Capital - Beate VölkerChapter 23: Social Support - Lijun Song and Zhe ZhangChapter 24: Corporate Networks - William K. Carroll, Jouke Huijzer and J. P. SapinskiChapter 25: International Trade Networks - Christina Prell, James Hollway, Petr Matous and Yasuyuki TodoPart 3Chapter 26: Centrality - M G Everett and S P BorgattiChapter 27: Structural Cohesion & Cohesive Groups - James Moody and Peter J. Mucha.Chapter 28: Multimodal social network analysis - Lorien JasnyChapter 29: Blockmodeling, Positions and Roles - Patrick Doreian, Anuška Ferligoj, and Vladimir BatageljChapter 30: Inferential Network Clustering with Hierarchical Bayesian Stochastic Blockmodels - Pierson Browne, Tyler Crick, and John McLeveyChapter 31: Personal Networks and Egocentric Analysis - Brea Perry, Adam Roth, and Mario SmallChapter 32: Multilevel Network Analysis - Emmanuel Lazega and Peng WangChapter 33:Exponential Random Graph Models - Johan KoskinenChapter 34: Network Dynamics - Tom A.B. Snijders and Christian E.G. SteglichChapter 35: Relational Event Models - Aaron Schecter and Noshir ContractorChapter 36: Latent Position Network Models - Hardeep Kaur, Riccardo Rastelli, Nial Friel and Adrian E. RafteryChapter 37: Negative Ties and Signed Networks - Filip AgneessensChapter 38: Qualitative and Mixed Methods - Betina HollsteinChapter 39: Spatial analysis of social networks - John R. HippChapter 40: Social Network Data Collection: Principles and Modalities - Jimi Adams and Miranda LubbersChapter 41: Missing Network Data - Robert W. Krause and Mark HuismanChapter 42: Scientific Software for Network Analysis - Pierson Browne, Adam Howe, Yasmin Koop-Monteiro, Yixi Yang, and John McLevey

John McLevey is an Associate Professor in the Department of Knowledge Integration at the University of Waterloo (ON, Canada). He is also appointed to the Departments of Sociology & Legal Studies and Geography and Environmental Management, is a Policy Fellow at the Balsillie School of International Affairs, and a Member of the Cybersecurity and Privacy Institute at the University of Waterloo. His work is funded by research grants from the Social Science and Humanities Research Council of Canada (SSHRC) and an Early Researcher Award from the Ontario Ministry of Research and Innovation. His current research project focuses on disinformation, censorship, and political deliberation in the public sphere across a wide variety of national contexts and political regimes. He wrote Doing Computational Social Science (SAGE Publishing, 2021) from his experiences as a researcher and advisor, as well as teaching courses in computational social science, data science, and research methods to students from diverse disciplinary backgrounds at the undergraduate and graduate level. John Scott is an Honorary Professor at the Universities of Essex, Exeter, and Copenhagen. He was formerly a professor of sociology at the Universities of Essex and Leicester, and pro-vice-chancellor for research at the University of Plymouth. He has been president of the British Sociological Association, Chair of the Sociology Section of the British Academy, and in 2013 was awarded the CBE for Services to Social Science. His work covers theoretical sociology, the history of sociology, elites and social stratification, and social network analysis. His most recent books include British Social Theory: Recovering Lost Traditions before 1950 (SAGE, 2018), Envisioning Sociology. Victor Branford, Patrick Geddes, and the Quest for Social Reconstruction (with Ray Bromley, SUNY Press, 2013), Objectivity and Subjectivity in Social Research (with Gayle Letherby and Malcolm Williams, SAGE, 2011).

• Chapter 1: Introduction - John Scott, John McLevey, and Peter J. CarringtonPart 1Chapter 2: Introducing Social Network Analysis - Christina Prell and David R. SchaeferChapter 3: Social Networks and Social Categories - Ronald Breiger and Robin Wagner-PacificiChapter 4: Social Networks and Computational Social Science - James A. Kitts, Helene Grogan and Kevin LewisChapter 5: Relational Sociology: Networks, Culture, and Interaction - Jan Fuhse and Ann MischePart 2Chapter 6: Social-ecological networks: What are they, why are they useful, and how can I use them? - Örjan BodinChapter 7: The Evolution of Environmental Policy Network Analysis - Tyler A. Scott, Mark Lubell and Gwen Arnold UC DavisChapter 8: Health Behaviors and Outcomes - Kayla de la HayeChapter 9: Political and policy networks - Mario DianiChapter 10: Social Movements and Collective Action - David TindallChapter 11: Gender and social networks - Elisa BellottiChapter 12: Why can’t we be friends? Understanding ethnic relations through network analysis - Rochelle CôtéChapter 13: Culture and Networks - Omar LizardoChapter 14: Semantic and Cultural Networks - Sarah Shugars and Sandra González-BailónChapter 15: Cognition and Social Networks - Matthew E. Brashears and Victoria MoneyChapter 16: Scientific Networks - Donghyun Kang and James EvansChapter 17: Crime and Networks - Marie Ouellet and Logan LedfordChapter 18: Historical Network Analysis: Two Problems of Scale - Ian KumekawaChapter 19: The Paradox of Behavior Change and the Science of Network Diffusion - Damon CentolaChapter 20: Network Interventions: Using Social Networks to Accelerate Diffusion of Innovations - Thomas W. ValenteChapter 21: Social Media and Digital Networks - Anabel Quan-Haase, Lyndsay Foisey and Riley McLaughlinChapter 22: Social Capital - Beate VölkerChapter 23: Social Support - Lijun Song and Zhe ZhangChapter 24: Corporate Networks - William K. Carroll, Jouke Huijzer and J. P. SapinskiChapter 25: International Trade Networks - Christina Prell, James Hollway, Petr Matous and Yasuyuki TodoPart 3Chapter 26: Centrality - M G Everett and S P BorgattiChapter 27: Structural Cohesion & Cohesive Groups - James Moody and Peter J. Mucha.Chapter 28: Multimodal social network analysis - Lorien JasnyChapter 29: Blockmodeling, Positions and Roles - Patrick Doreian, Anuška Ferligoj, and Vladimir BatageljChapter 30: Inferential Network Clustering with Hierarchical Bayesian Stochastic Blockmodels - Pierson Browne, Tyler Crick, and John McLeveyChapter 31: Personal Networks and Egocentric Analysis - Brea Perry, Adam Roth, and Mario SmallChapter 32: Multilevel Network Analysis - Emmanuel Lazega and Peng WangChapter 33:Exponential Random Graph Models - Johan KoskinenChapter 34: Network Dynamics - Tom A.B. Snijders and Christian E.G. SteglichChapter 35: Relational Event Models - Aaron Schecter and Noshir ContractorChapter 36: Latent Position Network Models - Hardeep Kaur, Riccardo Rastelli, Nial Friel and Adrian E. RafteryChapter 37: Negative Ties and Signed Networks - Filip AgneessensChapter 38: Qualitative and Mixed Methods - Betina HollsteinChapter 39: Spatial analysis of social networks - John R. HippChapter 40: Social Network Data Collection: Principles and Modalities - Jimi Adams and Miranda LubbersChapter 41: Missing Network Data - Robert W. Krause and Mark HuismanChapter 42: Scientific Software for Network Analysis - Pierson Browne, Adam Howe, Yasmin Koop-Monteiro, Yixi Yang, and John McLevey