Christian Borch is a professor of sociology at the University of Copenhagen. His current research focuses on automated trading in financial markets, exploring how machine learning is transforming market dynamics and leading to a reevaluation of sociological categories used to understand financial markets. His earlier historically focused work examined the development of sociological crowd theory and shifts in crime perceptions, both from the late nineteenth to the early twenty-first century. Before joining the University of Copenhagen, Borch was a Professor of Economic Sociology and Social Theory at the Copenhagen Business School.Juan Pablo Pardo-Guerra is a professor in sociology at the University of California, San Diego, a founding faculty member of the Halicio?lu Data Science Institute, co-founder of the Computational Social Science program, and Director of the Latin American Studies Program at UC San Diego. Prior to joining UC San Diego, Pardo-Guerra was an Assistant Professor atthe London School of Economics and Political Science.

• About the EditorsContributors Part I: Introduction: The Past, Present, and Future of Machine Learning in Sociology 1. Sociology and Machine Learning Juan Pablo Pardo-Guerra and Christian Borch 2. Machine Learning in Sociology: Current and Future ApplicationsFiliz Garip and Michael W. Macy 3. How Machine Learning Became PervasiveEmilio Lehoucq Part II: Machine Learning as a Methodological Toolbox 4. Corpus Modeling and the Geometries of Text: Meaning Spaces as Metaphor and MethodDustin S. Stoltz, Marissa A. Combs, and Marshall A. Taylor 5. Sociolinguistic Perspectives on Machine Learning with Textual DataAJ Alvero 6. Chinese Computational Sociology: Decolonial Applications of Machine Learning and Natural Language Processing Methods in Chinese-Language ContextsLinda Hong Cheng and Yao Lu 7. Hate Speech Detection and Bias in Supervised Text ClassificationThomas R. Davidson 8. Analyzing Image Data with Machine LearningHan Zhang 9. Sociogeographical Machine Learning: Using Machine Learning to Understand the Social Mechanisms of PlaceRolf Lyneborg Lund 10. The Machine Learning of Sound and Music in Sociological ResearchKe Nie 11. Munging the Ghosts in the Machine: Coded Bias and the Craft of Wrangling Archival DataVincent Yung and Jeannette A. Colyvas 12. Fitting Paradox: Machine Learning Algorithms vs Statistical ModelingEun Kyong Shin 13. Predictability Hypotheses: A Meta-Theoretical and Methodological IntroductionAustin van Loon 14. Ethnography and Machine Learning: Synergies and New DirectionsZhuofan Li and Corey M. Abramson 15. Machine Learning, Abduction, and Computational EthnographyPhilipp Brandt Part III: Societal Machine Learning Applications 16. Machine Learning, Infrastructures, and their Sociomaterial PossibilitiesJuan Pablo Pardo-Guerra 17. Race and Intersecting Inequalities in Machine LearningSharla Alegria 18. Gender, Sex, and the Constraints of Machine Learning MethodsJeffrey W. Lockhart 19. Facial Recognition in Law EnforcementJens Hälterlein 20. Machine Learning in Chinese courtsNyu Wang and Michael Yuan Tian 21. A Tale of Two Social Credit Systems: The Succeeded and Failed Adoption of Machine Learning in Sociotechnical InfrastructuresChuncheng Liu 22. Machine Learning as a State Building Experiment: AI and Development in AfricaYousif Hassan 23. The Use and Promises of Machine Learning in Financial Markets: From Mundane Practices to Complex Automated SystemsTaylor Spears and Kristian Bondo Hansen 24. Machine Learning and Large-scale Data for Understanding Urban InequalityJennifer Candipan and Jonathan Tollefson 25. Epistemic Infrastructures of Moral Decision-Making in the Ethics of Autonomous DrivingMaya Indira Ganesh 26. Machine Learning in Medical Systems: Toward a Sociological AgendaWanheng Hu 27. Machine Learning in the Arts and Cultural and Creative IndustriesMariya Dzhimova 28. Environment, Society, and Machine LearningCaleb Scoville, Hilary Faxon, Melissa Chapman, Samantha Jo Fried, Lily Xu, Carl Boettiger, J. Michael Reed, Marcus Lapeyrolerie, Amy Van Scoyoc, Razvan Amironesei 29. Coding and ExpertiseAlex Preda Part IV: Machine Learning and Sociological Theory 30. How Machine Learning is Reviving Sociological TheorizationLaura K. Nelson and Jessica J. Santana 31. Quality Control for Quality Computational Concepts: Wrangling with Theory and Data Wrangling as TheorizingVincent Yung, Jeannette A. Colyvas, and Hokyu Hwang 32. Machine Agencies: Large Language Models as a Case for a Sociology of MachinesCeyda Yolgörmez 33. Meaning and MachinesOscar Stuhler, Dustin S. Stoltz, and John Levi Martin 34. Machine Learning and the Analysis of CultureSophie Mützel and Étienne Ollion 35. Estimating Social Influence Using Machine Learning and Digital Trace DataMartin Arvidsson and Marc Keuschnigg 36. Computational Authority in Platform Society: Dimensions of Power in Machine LearningMassimo Airoldi 37. Predictive Analytics: A Sociological PerspectiveSimon Egbert 38. Theoretical Challenges of Human-Machine Interaction Towards a Sociology of InterfacesBenjamin Lipp and Henning Mayer 39. Colonialities of Machine LearningChristian Borch

Christian Borch is a professor of sociology at the University of Copenhagen. His current research focuses on automated trading in financial markets, exploring how machine learning is transforming market dynamics and leading to a reevaluation of sociological categories used to understand financial markets. His earlier historically focused work examined the development of sociological crowd theory and shifts in crime perceptions, both from the late nineteenth to the early twenty-first century. Before joining the University of Copenhagen, Borch was a Professor of Economic Sociology and Social Theory at the Copenhagen Business School.Juan Pablo Pardo-Guerra is a professor in sociology at the University of California, San Diego, a founding faculty member of the Halicio?lu Data Science Institute, co-founder of the Computational Social Science program, and Director of the Latin American Studies Program at UC San Diego. Prior to joining UC San Diego, Pardo-Guerra was an Assistant Professor atthe London School of Economics and Political Science.

• About the EditorsContributors Part I: Introduction: The Past, Present, and Future of Machine Learning in Sociology 1. Sociology and Machine Learning Juan Pablo Pardo-Guerra and Christian Borch 2. Machine Learning in Sociology: Current and Future ApplicationsFiliz Garip and Michael W. Macy 3. How Machine Learning Became PervasiveEmilio Lehoucq Part II: Machine Learning as a Methodological Toolbox 4. Corpus Modeling and the Geometries of Text: Meaning Spaces as Metaphor and MethodDustin S. Stoltz, Marissa A. Combs, and Marshall A. Taylor 5. Sociolinguistic Perspectives on Machine Learning with Textual DataAJ Alvero 6. Chinese Computational Sociology: Decolonial Applications of Machine Learning and Natural Language Processing Methods in Chinese-Language ContextsLinda Hong Cheng and Yao Lu 7. Hate Speech Detection and Bias in Supervised Text ClassificationThomas R. Davidson 8. Analyzing Image Data with Machine LearningHan Zhang 9. Sociogeographical Machine Learning: Using Machine Learning to Understand the Social Mechanisms of PlaceRolf Lyneborg Lund 10. The Machine Learning of Sound and Music in Sociological ResearchKe Nie 11. Munging the Ghosts in the Machine: Coded Bias and the Craft of Wrangling Archival DataVincent Yung and Jeannette A. Colyvas 12. Fitting Paradox: Machine Learning Algorithms vs Statistical ModelingEun Kyong Shin 13. Predictability Hypotheses: A Meta-Theoretical and Methodological IntroductionAustin van Loon 14. Ethnography and Machine Learning: Synergies and New DirectionsZhuofan Li and Corey M. Abramson 15. Machine Learning, Abduction, and Computational EthnographyPhilipp Brandt Part III: Societal Machine Learning Applications 16. Machine Learning, Infrastructures, and their Sociomaterial PossibilitiesJuan Pablo Pardo-Guerra 17. Race and Intersecting Inequalities in Machine LearningSharla Alegria 18. Gender, Sex, and the Constraints of Machine Learning MethodsJeffrey W. Lockhart 19. Facial Recognition in Law EnforcementJens Hälterlein 20. Machine Learning in Chinese courtsNyu Wang and Michael Yuan Tian 21. A Tale of Two Social Credit Systems: The Succeeded and Failed Adoption of Machine Learning in Sociotechnical InfrastructuresChuncheng Liu 22. Machine Learning as a State Building Experiment: AI and Development in AfricaYousif Hassan 23. The Use and Promises of Machine Learning in Financial Markets: From Mundane Practices to Complex Automated SystemsTaylor Spears and Kristian Bondo Hansen 24. Machine Learning and Large-scale Data for Understanding Urban InequalityJennifer Candipan and Jonathan Tollefson 25. Epistemic Infrastructures of Moral Decision-Making in the Ethics of Autonomous DrivingMaya Indira Ganesh 26. Machine Learning in Medical Systems: Toward a Sociological AgendaWanheng Hu 27. Machine Learning in the Arts and Cultural and Creative IndustriesMariya Dzhimova 28. Environment, Society, and Machine LearningCaleb Scoville, Hilary Faxon, Melissa Chapman, Samantha Jo Fried, Lily Xu, Carl Boettiger, J. Michael Reed, Marcus Lapeyrolerie, Amy Van Scoyoc, Razvan Amironesei 29. Coding and ExpertiseAlex Preda Part IV: Machine Learning and Sociological Theory 30. How Machine Learning is Reviving Sociological TheorizationLaura K. Nelson and Jessica J. Santana 31. Quality Control for Quality Computational Concepts: Wrangling with Theory and Data Wrangling as TheorizingVincent Yung, Jeannette A. Colyvas, and Hokyu Hwang 32. Machine Agencies: Large Language Models as a Case for a Sociology of MachinesCeyda Yolgörmez 33. Meaning and MachinesOscar Stuhler, Dustin S. Stoltz, and John Levi Martin 34. Machine Learning and the Analysis of CultureSophie Mützel and Étienne Ollion 35. Estimating Social Influence Using Machine Learning and Digital Trace DataMartin Arvidsson and Marc Keuschnigg 36. Computational Authority in Platform Society: Dimensions of Power in Machine LearningMassimo Airoldi 37. Predictive Analytics: A Sociological PerspectiveSimon Egbert 38. Theoretical Challenges of Human-Machine Interaction Towards a Sociology of InterfacesBenjamin Lipp and Henning Mayer 39. Colonialities of Machine LearningChristian Borch

Christian Borch is a professor of sociology at the University of Copenhagen. His current research focuses on automated trading in financial markets, exploring how machine learning is transforming market dynamics and leading to a reevaluation of sociological categories used to understand financial markets. His earlier historically focused work examined the development of sociological crowd theory and shifts in crime perceptions, both from the late nineteenth to the early twenty-first century. Before joining the University of Copenhagen, Borch was a Professor of Economic Sociology and Social Theory at the Copenhagen Business School.Juan Pablo Pardo-Guerra is a professor in sociology at the University of California, San Diego, a founding faculty member of the Halicio?lu Data Science Institute, co-founder of the Computational Social Science program, and Director of the Latin American Studies Program at UC San Diego. Prior to joining UC San Diego, Pardo-Guerra was an Assistant Professor atthe London School of Economics and Political Science.

• About the EditorsContributors Part I: Introduction: The Past, Present, and Future of Machine Learning in Sociology 1. Sociology and Machine Learning Juan Pablo Pardo-Guerra and Christian Borch 2. Machine Learning in Sociology: Current and Future ApplicationsFiliz Garip and Michael W. Macy 3. How Machine Learning Became PervasiveEmilio Lehoucq Part II: Machine Learning as a Methodological Toolbox 4. Corpus Modeling and the Geometries of Text: Meaning Spaces as Metaphor and MethodDustin S. Stoltz, Marissa A. Combs, and Marshall A. Taylor 5. Sociolinguistic Perspectives on Machine Learning with Textual DataAJ Alvero 6. Chinese Computational Sociology: Decolonial Applications of Machine Learning and Natural Language Processing Methods in Chinese-Language ContextsLinda Hong Cheng and Yao Lu 7. Hate Speech Detection and Bias in Supervised Text ClassificationThomas R. Davidson 8. Analyzing Image Data with Machine LearningHan Zhang 9. Sociogeographical Machine Learning: Using Machine Learning to Understand the Social Mechanisms of PlaceRolf Lyneborg Lund 10. The Machine Learning of Sound and Music in Sociological ResearchKe Nie 11. Munging the Ghosts in the Machine: Coded Bias and the Craft of Wrangling Archival DataVincent Yung and Jeannette A. Colyvas 12. Fitting Paradox: Machine Learning Algorithms vs Statistical ModelingEun Kyong Shin 13. Predictability Hypotheses: A Meta-Theoretical and Methodological IntroductionAustin van Loon 14. Ethnography and Machine Learning: Synergies and New DirectionsZhuofan Li and Corey M. Abramson 15. Machine Learning, Abduction, and Computational EthnographyPhilipp Brandt Part III: Societal Machine Learning Applications 16. Machine Learning, Infrastructures, and their Sociomaterial PossibilitiesJuan Pablo Pardo-Guerra 17. Race and Intersecting Inequalities in Machine LearningSharla Alegria 18. Gender, Sex, and the Constraints of Machine Learning MethodsJeffrey W. Lockhart 19. Facial Recognition in Law EnforcementJens Hälterlein 20. Machine Learning in Chinese courtsNyu Wang and Michael Yuan Tian 21. A Tale of Two Social Credit Systems: The Succeeded and Failed Adoption of Machine Learning in Sociotechnical InfrastructuresChuncheng Liu 22. Machine Learning as a State Building Experiment: AI and Development in AfricaYousif Hassan 23. The Use and Promises of Machine Learning in Financial Markets: From Mundane Practices to Complex Automated SystemsTaylor Spears and Kristian Bondo Hansen 24. Machine Learning and Large-scale Data for Understanding Urban InequalityJennifer Candipan and Jonathan Tollefson 25. Epistemic Infrastructures of Moral Decision-Making in the Ethics of Autonomous DrivingMaya Indira Ganesh 26. Machine Learning in Medical Systems: Toward a Sociological AgendaWanheng Hu 27. Machine Learning in the Arts and Cultural and Creative IndustriesMariya Dzhimova 28. Environment, Society, and Machine LearningCaleb Scoville, Hilary Faxon, Melissa Chapman, Samantha Jo Fried, Lily Xu, Carl Boettiger, J. Michael Reed, Marcus Lapeyrolerie, Amy Van Scoyoc, Razvan Amironesei 29. Coding and ExpertiseAlex Preda Part IV: Machine Learning and Sociological Theory 30. How Machine Learning is Reviving Sociological TheorizationLaura K. Nelson and Jessica J. Santana 31. Quality Control for Quality Computational Concepts: Wrangling with Theory and Data Wrangling as TheorizingVincent Yung, Jeannette A. Colyvas, and Hokyu Hwang 32. Machine Agencies: Large Language Models as a Case for a Sociology of MachinesCeyda Yolgörmez 33. Meaning and MachinesOscar Stuhler, Dustin S. Stoltz, and John Levi Martin 34. Machine Learning and the Analysis of CultureSophie Mützel and Étienne Ollion 35. Estimating Social Influence Using Machine Learning and Digital Trace DataMartin Arvidsson and Marc Keuschnigg 36. Computational Authority in Platform Society: Dimensions of Power in Machine LearningMassimo Airoldi 37. Predictive Analytics: A Sociological PerspectiveSimon Egbert 38. Theoretical Challenges of Human-Machine Interaction Towards a Sociology of InterfacesBenjamin Lipp and Henning Mayer 39. Colonialities of Machine LearningChristian Borch