Pathways between social science and computational social science: theories, methods, and interpretations
In: Computational Social Sciences
Intro -- Preface -- Contents -- Author Biographies -- Part I Theory: Dilemmas of Model Building and Interpretation -- Modeling the Complex Network of Social Interactions -- 1 Introduction -- 2 Characterization of Large-Scale Social Networks -- 2.1 Degree Distribution -- 2.2 Assortative Mixing by Degree -- 2.3 Clustering -- 2.4 Granovetterian Community Structure -- 2.5 Tie Formation and Fading -- 2.6 Multiplex Structure and Overlapping Communities -- 3 Modeling Granovetterian Community Structure -- 3.1 Weighted Social Network -- 3.2 Link Expiration -- 3.3 Multiplex Structure -- 4 Homophily and Structural Changes -- 5 Summary and Outlook -- References -- Formal Design Methods and the Relation Between Simulation Models and Theory: A Philosophy of Science Point of View -- 1 Introduction -- 2 Formal Design Methods for Agent-Based Simulation -- 2.1 An ODD Protocol for Abelson's and Bernstein's Early Work -- 2.2 Other Approaches -- 3 The `Non-statement View' of Structuralism -- 4 Translation into a New Simulation Model -- 4.1 Designing Agent Types, Relations and Functions -- 4.2 Results -- 5 Conclusion and Outlook -- References -- Part II Methodological Toolsets -- The Potential of Automated Text Analytics in Social KnowledgeBuilding -- 1 Introduction -- 2 Challenges -- 3 A New Methodological Basis of Sociology -- 3.1 New Data Sources -- 3.2 A Brief Overview of NLP Methods -- 3.2.1 Pre-processing -- 3.2.2 Bag of Words and Beyond -- 3.3 The Goal of the Analysis and the Corresponding NLP Methods -- 3.3.1 Supervised Methods -- 3.3.2 Unsupervised Methods -- 3.3.3 Which Method to Choose -- 4 New Possibilities for Sociological Research -- 4.1 How to Approach Automated Text Analysis as a Social Scientist -- 4.2 Combining the New with the Traditional: Mixed Approaches -- 4.3 What the Approach Can Offer to Classic Sociological Questions -- 5 Summary.