We Are All Social Scientists Now
How Big Data, Machine Learning, and Causal Inference Work Together
Bibliographic Data
| ID | 6096551 |
|---|---|
| Authors | Justin Grimmer (0000-0001-6642-9799, Stanford University, corresponding author) |
| Year | 2015 |
| Volume | 48 |
| Issue | 1 |
| Pages | 80-83 |
| Publication date | 2015-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | PS Political Science & Politics (JOURNAL) |
| Journal identifiers | ISSN: 1049-0965 • E-ISSN: 1537-5935 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s1049096514001784 |
| OpenAlex | W2102995204 |
| Language | EN |
| Citations received | 56 |
| References cited | 28 |
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Big data · Causal inference · Data mining · Data science · Econometrics · Economics · Inference · Political science · Computational and Text Analysis Methods · Computer Science · Data Analysis with R · Engineering · Qualitative Comparative Analysis Research · Artificial Intelligence
Soziologie des Digitalen - Digitale Soziologie?
Com a palavra os nobres deputados
Analytical sociology and computational social science
Big Data and Trust in Public Policy Automation
Finding the Missing Atheists
Toward a Qualitative Study of the American Voter
Big data e as pegadas do monstro
La sociología a través de sus publicaciones en revistas de impacto mediante el uso de big data
I Saw You in the Crowd
Improving Content Analysis
Training Computational Social Science PhD Students for Academic and Non-Academic Careers
Can We Algorithmize Politics? The Promise and Perils of Computerized Text Analysis in Political Research
Big Data, Causal Inference, and Formal Theory
The Multiclass Classification of Newspaper Articles with Machine Learning
From the exotic to the everyday
Utilizing predictive modeling to enhance policy and practice through improved identification of at-risk clients
Randomized experiments by government institutions and American political development
"Big Data" in Economic History
Com a Palavra os Nobres Deputados
Spontaneous Collective Action
Discretion in the Surveillance State
A Review of Best Practice Recommendations for Text Analysis in R (and a User-Friendly App)
Benefits and applications of interdisciplinary digital tools for environmental meta-reviews and analyses
Big Data
Machine learning and public health policy evaluation
Social Work Data Corps Project
Expressing Uncertainty and Risk About the Mpox Outbreak
From Utopia Through Dystopia
Social prediction
Performance of the South American Defense Council Under Autonomy Pressures
Persuasion with Precision
A place to stand
Understanding crisis communication on social media with Cerc
L'utilizzo dei big social data per la ricerca sociale
Gender Equality, Governance and National Innovation Capability for Sustainable Development
Rhetorical and phraseological features of research article introductions
Working the fields of big data
Content Analysis of Digital Text and Its Applications
Learning about Spatial and Temporal Proximity using Tree-Based Methods
The emergence of computational social science
Big Tigers, Big Data”
What Are the Salient and Memorable Green-Restaurant Attributes? Capturing Customer Perceptions From User-Generated Content
A Diachronic Analysis of the Citational Practice of Comparing
A review of data-intensive approaches for sustainability
Values, challenges and future directions of big data analytics in healthcare
From Text Signals to Simulations
Digital divide and beyond
The Nodality Disconnect of Data-Driven Government
Causal Inferences from Digital Behavioral Data
Comparing Online and Offline Political Support
Why are the affluent better represented around the world
Causal inference in political science research
Re-imagining the Cambridge School in the Age of Digital Humanities
Data science for social work practice
Varieties of political support in emerging democracies
An Application of Machine Learning for Predicting Rearrests
Making the News
Party Polarization in Congress
Do Voters Affect or Elect Policies? Evidence from the U. S. House
Misunderstandings Between Experimentalists and Observationalists about Causal Inference
Estimating treatment effect heterogeneity in randomized program evaluation
The central role of the propensity score in observational studies for causal effects
Pivotal Politics
Structural Topic Models for Open‐Ended Survey Responses
Dividers, Not Uniters
The Polarization of American Politics
Modeling Heterogeneous Treatment Effects in Survey Experiments with Bayesian Additive Regression Trees
Blocking for Sequential Political Experiments
Text as Data
Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference
To Simulate or Nominate
Opiates for the Matches
Mapping the Ideological Marketplace
A Spatial Model for Legislative Roll Call Analysis
Does Gerrymandering Cause Polarization
How to Analyze Political Attention with Minimal Assumptions and Costs
Mere Description
Causality in Political Networks
Drawing Inferences and Testing Theories with Big Data
No! Formal Theory, Causal Inference, and Big Data Are Not Contradictory Trends in Political Science
Analyzing Big Data
Quantifying Social Media's Political Space
The Statistical Analysis of Roll Call Data
| Unique citing works | 56 |
|---|---|
| Citations per year | 5,09 |
| Citation span | 2015 - 2026 (12) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 36 |