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Provides an introduction to the major theories, methods and findings of social network analysis research and the applications from that research.
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Provides an introduction to the major theories, methods and findings of social network analysis research and the applications from that research.
Produktdetails
- Produktdetails
- Verlag: SAGE Publications Inc
- Seitenzahl: 344
- Erscheinungstermin: 14. März 2013
- Englisch
- Abmessung: 235mm x 191mm x 19mm
- Gewicht: 642g
- ISBN-13: 9781412999472
- ISBN-10: 1412999472
- Artikelnr.: 36530515
- Verlag: SAGE Publications Inc
- Seitenzahl: 344
- Erscheinungstermin: 14. März 2013
- Englisch
- Abmessung: 235mm x 191mm x 19mm
- Gewicht: 642g
- ISBN-13: 9781412999472
- ISBN-10: 1412999472
- Artikelnr.: 36530515
Brian V. Carolan is Associate Professor of Quantitative Research Methods at Montclair State University. Prior to joining Montclair State University in 2010, he was Associate Professor of Social Foundations of Education in the Department of Education, College of Staten Island, CUNY. He received his B.A. in sociology from Rutgers University, M.Phil in sociology from Columbia University, and his Ph.D. in sociology and education from Teachers College, Columbia University. Brian has published widely in a variety of areas related to education, covering issues such as high school size, grade span configuration, and the social organization of classrooms. This diversity of topical interests reflects his desire to employ methodological strategies from different disciplines to examine phenomena that are of interest to educational stakeholders. Consequently, his work has appeared in diverse outlets, including Social Networks, Educational Researcher, Teachers College Record, Journal of Research on Adolescence, and others. He currently teaches graduate-level research methods courses to students in the educational and health services fields.
Part I. Theory and Concepts
Chapter 1. The Social Network Perspective and Educational Research
Chapter 2. Historical, Theoretical, and Analytical Foundations
Chapter 3. Basic Concepts
Part II. Methods and Measures
Chapter 4. Collecting and Managing Network Data
Chapter 5. Structural Measures for Complete Networks
Chapter 6. Groups and Positions in Complete Networks
Chapter 7. Measures for Egocentric Networks
Part III. Applications and Examples
Chapter 8. An Introduction to Statistical Inference with Network Data
Chapter 9. Network Data and Statistical Models
Chapter 10. Social Capital
Chapter 11. Diffusion
Chapter 12. Looking Back, Looking Ahead
Chapter 1. The Social Network Perspective and Educational Research
Chapter 2. Historical, Theoretical, and Analytical Foundations
Chapter 3. Basic Concepts
Part II. Methods and Measures
Chapter 4. Collecting and Managing Network Data
Chapter 5. Structural Measures for Complete Networks
Chapter 6. Groups and Positions in Complete Networks
Chapter 7. Measures for Egocentric Networks
Part III. Applications and Examples
Chapter 8. An Introduction to Statistical Inference with Network Data
Chapter 9. Network Data and Statistical Models
Chapter 10. Social Capital
Chapter 11. Diffusion
Chapter 12. Looking Back, Looking Ahead
Part I. Theory and Concepts
Chapter 1. The Social Network Perspective and Educational Research
Chapter 2. Historical, Theoretical, and Analytical Foundations
Chapter 3. Basic Concepts
Part II. Methods and Measures
Chapter 4. Collecting and Managing Network Data
Chapter 5. Structural Measures for Complete Networks
Chapter 6. Groups and Positions in Complete Networks
Chapter 7. Measures for Egocentric Networks
Part III. Applications and Examples
Chapter 8. An Introduction to Statistical Inference with Network Data
Chapter 9. Network Data and Statistical Models
Chapter 10. Social Capital
Chapter 11. Diffusion
Chapter 12. Looking Back, Looking Ahead
Chapter 1. The Social Network Perspective and Educational Research
Chapter 2. Historical, Theoretical, and Analytical Foundations
Chapter 3. Basic Concepts
Part II. Methods and Measures
Chapter 4. Collecting and Managing Network Data
Chapter 5. Structural Measures for Complete Networks
Chapter 6. Groups and Positions in Complete Networks
Chapter 7. Measures for Egocentric Networks
Part III. Applications and Examples
Chapter 8. An Introduction to Statistical Inference with Network Data
Chapter 9. Network Data and Statistical Models
Chapter 10. Social Capital
Chapter 11. Diffusion
Chapter 12. Looking Back, Looking Ahead