Pathways Between Social Science and Computational Social Science

This volume shows that the emergence of computational social science (CSS) is an endogenous response to problems from within the social sciences and not exogeneous. The three parts of the volume address various pathways along which CSS has been developing from and interacting with existing research frameworks. The first part exemplifies how new theoretical models and approaches on which CSS research is based arise from theories of social science. The second part is about methodological advances facilitated by CSS-related techniques. The third part illustrates the contribution of CSS to traditional social science topics, further attesting to the embedded nature of CSS. The expected readership of the volume includes researchers with a traditional social science background who wish to approach CSS, experts in CSS looking for substantive links to more traditional social science theories, methods and topics, and finally, students working in both fields.

Auteur

Tamás Rudas is Professor of Statistics in the Faculty of Social Sciences of the Eötvös Loránd University, Budapest. His main field of research is the development of methods of mathematical statistics and their applications in the social sciences.
Gábor L. Péli is a senior researcher at the Centre for Social Sciences, Hungarian Academy of Sciences Centre for Excellence and professor of sociology at the Károli Gáspár University of the Reformed Church in Hungary. His research interests are in the logical analysis of organizational discourse and behavior along with network approaches to organizations.

Contenu

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