Publisher | Springer, Berlin |
Year | |
Pages | 275 |
Version | hardback |
Language | English |
ISBN | 9783030549350 |
Categories | Society & social sciences |
Pathways Between Social Science and Computational Social Science: Theories, Methods, and Interpretations
INTRODUCTION
The impact of Computational Social Science on the Social Sciences:
PART A: THEORY - DILEMMAS OF MODEL BUILDING AND INTERPRETATION
From Big Data to some deep thoughts - and back
Data driven modeling of complex networks of social interactions: Insight from ten years of explorative research
Formal design methods and the relation between simulation models and theory: A philosophy of science point of view
The social construction of knowledge in networks: Model testing with Dynamic Epistemic Logics
PART B: METHODOLOGICAL TOOLSETS
Discovering sociological knowledge through automated text analytics: Redefining the methodological foundations of sociology?
Combining scientific and non-scientific surveys to improve estimation and reduce costs
Harnessing the power of data science to grasp insights about human behavior, thinking and feeling from social media images
Computational modeling of characteristics conceptualized in an oppositional structure
PART C: NEW LOOK ON OLD ISSUES - RESEARCH DOMAINS REVISITED BY COMPUTATIONAL SOCIAL SCIENCE
Modeling gender (im)balance in the Big Data era: A novel spatio-temporal approach to latent variables
Agent-based organizational ecologies: Algorithmic approaches to study market structuration and evolution
"Who is your best friend in the Politburo?" Possibilities and restrictions of historical network research
Participatory budgeting algorithms
From Durkheim to machine learning: Finding the relevant sociological content related to in a social media discourse
EPILOGUE
Changing understanding in algorithmic societies: Exploring a new perception of social reality with Computational Social Science