Machine learning for social science: An agnostic approach
J Grimmer, ME Roberts… - Annual Review of Political …, 2021 - annualreviews.org
Social scientists are now in an era of data abundance, and machine learning tools are
increasingly used to extract meaning from data sets both massive and small. We explain …
increasingly used to extract meaning from data sets both massive and small. We explain …
Machine learning for sociology
Machine learning is a field at the intersection of statistics and computer science that uses
algorithms to extract information and knowledge from data. Its applications increasingly find …
algorithms to extract information and knowledge from data. Its applications increasingly find …
We are all social scientists now: How big data, machine learning, and causal inference work together
J Grimmer - PS: Political Science & Politics, 2015 - cambridge.org
Information is being produced and stored at an unprec-edented rate. It might come from
recording the public's daily life: people express their emotions on Facebook accounts, tweet …
recording the public's daily life: people express their emotions on Facebook accounts, tweet …
[图书][B] Computational social science
RM Alvarez - 2016 - books.google.com
Quantitative research in social science research is changing rapidly. Researchers have vast
and complex arrays of data with which to work: we have incredible tools to sift through the …
and complex arrays of data with which to work: we have incredible tools to sift through the …
Integrating explanation and prediction in computational social science
Computational social science is more than just large repositories of digital data and the
computational methods needed to construct and analyse them. It also represents a …
computational methods needed to construct and analyse them. It also represents a …
How to make causal inferences using texts
Text as data techniques offer a great promise: the ability to inductively discover measures
that are useful for testing social science theories with large collections of text. Nearly all text …
that are useful for testing social science theories with large collections of text. Nearly all text …
No! Formal theory, causal inference, and big data are not contradictory trends in political science
As with any high fashion, the beauty and horror of “big data” 1 is in the eye of the beholder.
The ques-tion that prompted the present symposium—“Are formal theory, causal inference …
The ques-tion that prompted the present symposium—“Are formal theory, causal inference …
A hierarchy of limitations in machine learning
MM Malik - arXiv preprint arXiv:2002.05193, 2020 - arxiv.org
" All models are wrong, but some are useful", wrote George EP Box (1979). Machine
learning has focused on the usefulness of probability models for prediction in social …
learning has focused on the usefulness of probability models for prediction in social …
The challenge of big data and data science
HE Brady - Annual Review of Political Science, 2019 - annualreviews.org
Big data and data science are transforming the world in ways that spawn new concerns for
social scientists, such as the impacts of the internet on citizens and the media, the …
social scientists, such as the impacts of the internet on citizens and the media, the …
Prediction and explanation in social systems
Historically, social scientists have sought out explanations of human and social phenomena
that provide interpretable causal mechanisms, while often ignoring their predictive accuracy …
that provide interpretable causal mechanisms, while often ignoring their predictive accuracy …