scholarly journals Intelligent Management of Data Driven Simulations to Support Model Building in the Social Sciences

2006 ◽  
pp. 562-569 ◽  
Author(s):  
Catriona Kennedy ◽  
Georgios Theodoropoulos
Keyword(s):  
Social Sciences ◽  
Model Building ◽  
Data Driven ◽  
The Social ◽  
Intelligent Management ◽  
Support Model

scholarly journals Data Driven Simulation to Support Model Building in the Social Sciences

2011 ◽  
Vol 5 (4) ◽  
pp. 561-581 ◽  
Author(s):  
Catriona Kennedy ◽  
Georgios Theodoropoulos ◽  
Volker Sorge ◽  
Edward Ferrari ◽  
Peter Lee ◽  
...  
Keyword(s):  
Social Sciences ◽  
Model Building ◽  
Data Driven ◽  
The Social ◽  
Support Model

Social Ontology and Model-Building: A Response to Epstein

2021 ◽  
Vol 51 (2) ◽  
pp. 176-192
Author(s):  
Nadia Ruiz
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Model Building ◽  
Social Ontology ◽  
Model Construction ◽  
Ontological Commitments ◽  
Starting Point ◽  
The Social

Brian Epstein has recently argued that a thoroughly microfoundationalist approach towards economics is unconvincing for metaphysical reasons. Generally, Epstein argues that for an improvement in the methodology of social science we must adopt social ontology as the foundation of social sciences; that is, the standing microfoundationalist debate could be solved by fixing economics’ ontology. However, as I show in this paper, fixing the social ontology prior to the process of model construction is optional instead of necessary and that metaphysical-ontological commitments are often the outcome of model construction, not its starting point. By focusing on the practice of modeling in economics the paper provides a useful inroad into the debate about the role of metaphysics in the natural and social sciences more generally.

Stochastic Actor-Oriented Models for the Co-Evolution of Networks and Behavior: An Introduction and Tutorial

2019 ◽  
Vol 23 (3) ◽  
pp. 511-534 ◽  
Author(s):  
Yuval Kalish
Keyword(s):  
Social Sciences ◽  
Model Building ◽  
Network Evolution ◽  
Network Ties ◽  
Network Change ◽  
Step Model ◽  
The Social ◽  
Research Questions ◽  
Organizational Scholarship ◽  
And Behavior

Stochastic actor-oriented (SAO) models are a family of models for network dynamics that enable researchers to test multiple, often competing explanations for network change and estimate the extent and relative power of various influences on network evolution. SAO models for the co-evolution of network ties and actor behavior, the most comprehensive category of SAO models, examine how networks and actor attributes—their behavior, performance, or attitudes—influence each other over time. While these models have been widely used in the social sciences, and particularly in educational settings, their use in organizational scholarship has been extremely limited. This paper provides a layperson introduction to SAO models for the co-evolution of networks and behavior and the types of research questions they can address. The models and their underpinnings are explained in nonmathematical terms, and theoretical explanations are supported by a concrete, detailed example that includes step-by-step model building and hypothesis testing, alongside an R script.

Model Building in the Social Sciences.

1970 ◽  
Vol 133 (3) ◽  
pp. 488
Author(s):  
G. R. Fisher ◽  
Roger Peltier
Keyword(s):  
Social Sciences ◽  
Model Building ◽  
The Social

scholarly journals O fim da teoria: o confronto entre a pesquisa orientada por dados e a pesquisa orientada por hipóteses | The end of theory: the confrontation between data-driven research and hypothesis-driven research

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Luís Fernando Sayão ◽  
Luana Farias Sales
Keyword(s):  
Social Sciences ◽  
Big Data ◽  
Scientific Method ◽  
Computational Analysis ◽  
Data Driven ◽  
Present Essay ◽  
Contemporary Science ◽  
The Social ◽  
Analysis Strategies ◽  
New Knowledge

RESUMO A ciência contemporânea e seus fundamentos metodológicos têm sido impactados pelo fenômeno do big data, que proclama que na era dos dados medidos em petabytes, de supercomputadores e sofisticados algoritmos, o método científico está obsoleto e que as hipóteses e modelos estão superados. As estratégias do big data científico confia em estratégias de análises computacionais de massivas quantidades de dados para revelar correlações, padrões e regras que vão gerar novos conhecimentos, que vão das ciências exatas até as ciências sociais, humanidade e cultura, delineando um arquétipo de ciência orientada por dados. O presente ensaio coloca em pauta as controvérsias em torno da ciência orientada por dados em contraposição à ciência orientada por hipóteses, e analisa alguns dos desdobramentos desse embate epistemológico. Para tal, tomo como metodologia os escritos de alguns autores mais proximamente envolvidos nessa questão.Palavras-chave: Big Data; Método Cientifico; Ciência Orientada por Dados; Ciência Orientada por Hipóteses.ABSTRACT Contemporary science and its methodological foundations have been impacted by the big data phenomenon that proclaims that in the age of data measured in petabytes, supercomputers and sophisticated algorithms the scientific method is obsolete and that the hypotheses and models are outdated.The strategies of the scientific big data rely on computational analysis strategies of massive amounts of data to reveal correlations, patterns and rules that will generate new knowledge, ranging from the exact sciences to the social sciences, humanity and culture, outlining an archetype of data-driven science. The present essay addresses the debates around data-driven science as opposed to hypothesis-oriented science and analyzes some of the ramifications of this epistemological confrontation. For this, the writings of some authors who are more closely involved in this question are taken as methodology.Keywords: Big Data; Scientific Method; Data-Driven Science; Hypothesis-Driven Science.

scholarly journals Supporting theoretically-grounded model building in the social sciences through interactive visualisation

2017 ◽  
Vol 268 ◽  
pp. 153-163 ◽  
Author(s):  
Cagatay Turkay ◽  
Aidan Slingsby ◽  
Kaisa Lahtinen ◽  
Sarah Butt ◽  
Jason Dykes
Keyword(s):  
Social Sciences ◽  
Model Building ◽  
The Social ◽  
Interactive Visualisation
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