Machine Learning in Social Science
portes grátis
Machine Learning in Social Science
Applications and Advances
Chen, Zhuo; Ma, Wen; Ju, Guodong; Chen, Yunsong
Springer Verlag, Singapore
04/2026
363
Dura
Inglês
9789819564644
Pré-lançamento - envio 15 a 20 dias após a sua edição
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Chapter 1: Introduction: The Rise of Machine Learning in Social Science.- Part I: Basics of Machine Learning for Social Science.- Chapter 2: Social Prediction: A New Research Paradigm Based on Supervised Machine Learning.- Chapter 3: Modeling Massive: Discovering Structure using Unsupervised Machine Learning.- Part II: Measuring the Unmeasurable.- Chapter 4: Unspeakable Violence: Predicting the Incidence of Intimate Partner Violence.- Chapter 5: Hidden Identities: Predicting Sexual Minority Orientation among Youth.- Part III: Developing Theories.- Chapter 6: Computing Grounded Theory: Algorithmic Approaches to Theory Construction.- Chapter 7: Applications of Computing Grounded Theory: Revisiting Subjective Well-being.- Part IV: Identifying Causality.- Chapter 8: Enhancing Traditional Methods of Causal Inference using Machine Learning: Optimizing Matching, Instrumental Variables, and Quasi-Experiments.- Chapter 9: Double Machine Learning for Causal Inference on High-Dimensional Data: A Flexible and Robust Approach to Causal Estimation.- Part V: Modeling Topics.- Chapter 10: Modeling Gender Consciousness: Women Authors' Creation in Boys' Love Fiction.- Chapter 11: Modeling Ideology: A Distant Reading of Marx/Engels Collected Works.- Part VI: Modeling Sentiments.- Chapter 12: From Barbarism to Civilization: The Evolving Image of China in International Cinema.- Chapter 13: A United Tale of Three Regions: A Century of China on Screen.
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Open Access;Computational sociology;digital humanities;topic modeling; causal inference using machine learning;text mining;social prediction;sentiment analysis
Chapter 1: Introduction: The Rise of Machine Learning in Social Science.- Part I: Basics of Machine Learning for Social Science.- Chapter 2: Social Prediction: A New Research Paradigm Based on Supervised Machine Learning.- Chapter 3: Modeling Massive: Discovering Structure using Unsupervised Machine Learning.- Part II: Measuring the Unmeasurable.- Chapter 4: Unspeakable Violence: Predicting the Incidence of Intimate Partner Violence.- Chapter 5: Hidden Identities: Predicting Sexual Minority Orientation among Youth.- Part III: Developing Theories.- Chapter 6: Computing Grounded Theory: Algorithmic Approaches to Theory Construction.- Chapter 7: Applications of Computing Grounded Theory: Revisiting Subjective Well-being.- Part IV: Identifying Causality.- Chapter 8: Enhancing Traditional Methods of Causal Inference using Machine Learning: Optimizing Matching, Instrumental Variables, and Quasi-Experiments.- Chapter 9: Double Machine Learning for Causal Inference on High-Dimensional Data: A Flexible and Robust Approach to Causal Estimation.- Part V: Modeling Topics.- Chapter 10: Modeling Gender Consciousness: Women Authors' Creation in Boys' Love Fiction.- Chapter 11: Modeling Ideology: A Distant Reading of Marx/Engels Collected Works.- Part VI: Modeling Sentiments.- Chapter 12: From Barbarism to Civilization: The Evolving Image of China in International Cinema.- Chapter 13: A United Tale of Three Regions: A Century of China on Screen.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
