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We Are All Social Scientists Now: How Big Data, Machine Learning, and Causal Inference Work Together

Grimmer, Justin

PS, political science & politics, 2015-01, Vol.48 (1), p.80-83 [Periódico revisado por pares]

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Título:
We Are All Social Scientists Now: How Big Data, Machine Learning, and Causal Inference Work Together
Autor: Grimmer, Justin
Assuntos: Artificial intelligence ; Causality ; Computers ; Data ; Data analysis ; Data collection ; Experiments ; Inference ; Political Scientists ; Research Design ; Revolutions ; Social Sciences ; Social Scientists ; Symposium: Big Data, Causal Inference, and Formal Theory: Contradictory Trends in Political Science?
É parte de: PS, political science & politics, 2015-01, Vol.48 (1), p.80-83
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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Descrição: Information is being produced and stored at an unprecedented rate. The promise of the "big data" revolution is that in these data are the answers to fundamental questions of businesses, governments, and social sciences. Grimmer argues that big data provides the opportunity to learn about quantities that were infeasible only a few years ago. The opportunity for descriptive inference creates the chance for political scientists to ask causal questions and create new theories that previously would have been impossible.
Editor: New York, USA: Cambridge University Press
Idioma: Inglês

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