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Many applications of computational social science aim to infer causal conclusions from non-experimental data.
Using text embeddings for causal inference
Victor Veitch, Dhanya Sridhar, and David M Blei. 2019 · 1905
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Estimating causal effects of treatments in randomized and nonrandomized studies
Donald B Rubin. 1974 · 1974
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The central role of the propensity score in observational studies for causal effects
Paul R Rosenbaum and Donald B Rubin. 1983 · 1983
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Reducing bias in observational studies using subclassification on the propensity score
Paul R Rosenbaum and Donald B Rubin. 1984 · 1984
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Statistics and causal inference
Paul W Holland. 1986 · 1986
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Evaluating the econometric evaluations of training programs with experimental data
Robert J LaLonde. 1986 · 1986
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Measurement Error Models
Wayne A Fuller. 1987 · 1987
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The role of the propensity score in estimating dose-response functions
Guido W Imbens. 2000 · 2000
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Causal discovery from medical textual data
Subramani Mani and Gregory F Cooper. 2000 · 2000
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Causality: Models, Reasoning and Inference
Judea Pearl. 2000 · 2000
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Linguistic inquiry and word count: Liwc 2001
James W Pennebaker, Martha E Francis, and Roger J Booth. 2001 · 2001
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Using propensity scores to help design observational studies: application to the tobacco litigation
Donald B Rubin. 2001 · 2001
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Latent Dirichlet Allocation
David M Blei, Andrew Y Ng, and Michael I Jordan. 2003 · 2003
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Implementing matching estimators for average treatment effects in stata
Alberto Abadie, David Drukker, Jane Leber Herr, and Guido W Imbens. 2004 · 2004
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Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study
Jared K Lunceford and Marie Davidian. 2004 · 2004
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Causal inference using potential outcomes: Design, modeling, decisions
Donald B Rubin. 2005 · 2005
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Measurement Error in Nonlinear Models: a Modern Perspective
Raymond J Carroll, David Ruppert, Leonard A Stefanski, and Ciprian M Crainiceanu. 2006 · 2006
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Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference
Daniel E Ho, Kosuke Imai, Gary King, and Elizabeth A Stuart. 2007 · 2007
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Some practical guidance for the implementation of propensity score matching
Marco Caliendo and Sabine Kopeinig. 2008 · 2008
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Can nonrandomized experiments yield accurate answers? A randomized experiment comparing random and nonrandom assignments
William R Shadish, Margaret H Clark, and Peter M Steiner. 2008 · 2008
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Evaluation methods for topic models
Hanna M Wallach, Iain Murray, Ruslan Salakhutdinov, and David Mimno. 2009 · 2009
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Measurement Error: Models, Methods, and Applications
John P Buonaccorsi. 2010 · 2010
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Matching methods for causal inference: A review and a look forward
Elizabeth A Stuart. 2010 · 2010
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Targeted Learning: Causal Inference for Observational and Experimental Data
Mark J Van der Laan and Sherri Rose. 2011 · 2011
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Covariate selection in high-dimensional propensity score analyses of treatment effects in small samples
Jeremy A Rassen, Robert J Glynn, M Alan Brookhart, and Sebastian Schneeweiss. 2011 · 2011
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Causal inference without balance checking: Coarsened exact matching
Stefano M Iacus, Gary King, and Giuseppe Porro. 2012 · 2012
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The garden of forking paths: Why multiple comparisons can be a problem, even when there is no “fishing expedition” or “p-hacking” and the research hypothesis was posited ahead of time
Andrew Gelman and Eric Loken. 2013 · 2013
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Front-door versus back-door adjustment with unmeasured confounding: Bias formulas for front-door and hybrid adjustments
Adam Glynn and Konstantin Kashin. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Single world intervention graphs (SWIGs): A unification of the counterfactual and graphical approaches to causality
Thomas S Richardson and James M Robins. 2013 · 2013
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Care and feeding of topic models: Problems, diagnostics, and improvements
Jordan Boyd-Graber, David Mimno, and David Newman. 2014 · 2014
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Endogenous selection bias: The problem of conditioning on a collider variable
Felix Elwert and Christopher Winship. 2014 · 2014
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Measurement bias and effect restoration in causal inference
Manabu Kuroki and Judea Pearl. 2014 · 2014
Cited alongside, same era.
Interpretation and identification of causal mediation
Judea Pearl. 2014 · 2014
Cited alongside, same era.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Cited alongside, same era.
Structural topic models for open-ended survey responses
Margaret E Roberts, Brandon M Stewart, Dustin Tingley, Christopher Lucas, Jetson Leder-Luis, Shana Kushner Gadarian, Bethany Albertson, and David G Rand. 2014 · 2014
Cited alongside, same era.
The effect of wording on message propagation: Topic-and author-controlled natural experiments on twitter
Chenhao Tan, Lillian Lee, and Bo Pang. 2014 · 2014
Cited alongside, same era.
Low resource dependency parsing: Cross-lingual parameter sharing in a neural network parser
Thai T Pham and Yuanyuan Shen. 2017 · 2017
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Bit By Bit: Social Research in the Digital Age
Matthew Salganik. 2017 · 2017
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Pulling out the stops: Rethinking stopword removal for topic models
Alexandra Schofield, Måns Magnusson, and David Mimno. 2017 · 2017
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Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2017 · 2017
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Evaluating the stability of embedding-based word similarities
Maria Antoniak and David Mimno. 2018 · 2018
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Long Duong, Trevor Cohn, Steven Bird, and Paul Cook. 2015 · 2015
Cited alongside, same era.
Causal Inference in Statistics, Social, and Biomedical Sciences
Guido W Imbens and Donald B Rubin. 2015 · 2015
Cited alongside, same era.
Deep unordered composition rivals syntactic methods for text classification
Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, and Hal Daumé III. 2015 · 2015
Cited alongside, same era.
Improving distributional similarity with lessons learned from word embeddings
Omer Levy, Yoav Goldberg, and Ido Dagan. 2015 · 2015
Cited alongside, same era.
Counterfactuals and Causal Inference
Stephen L Morgan and Christopher Winship. 2015 · 2015
Cited alongside, same era.
Posterior calibration and exploratory analysis for natural language processing models
Khanh Nguyen and Brendan O’Connor. 2015 · 2015
Cited alongside, same era.
Evaluation methods for unsupervised word embeddings
Tobias Schnabel, Igor Labutov, David Mimno, and Thorsten Joachims. 2015 · 2015
Cited alongside, same era.
Proceedings of the Third Workshop on Representation Learning for NLP
Isabelle Augenstein, Kris Cao, He He, Felix Hill, Spandana Gella, Jamie Kiros, Hongyuan Mei, and Dipendra Misra. 2018 · 2018
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The importance of calibration for estimating proportions from annotations
Dallas Card and Noah A Smith. 2018 · 2018
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Text preprocessing for unsupervised learning: Why it matters, when it misleads, and what to do about it
Matthew J Denny and Arthur Spirling. 2018 · 2018
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Uncertainty-aware generative models for inferring document class prevalence
Katherine Keith and Brendan O’Connor. 2018 · 2018
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Using longitudinal social media analysis to understand the effects of early college alcohol use
Emre Kiciman, Scott Counts, and Melissa Gasser. 2018 · 2018
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How conditioning on posttreatment variables can ruin your experiment and what to do about it
Jacob M Montgomery, Brendan Nyhan, and Michelle Torres. 2018 · 2018
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Sentence encoders on stilts: Supplementary training on intermediate labeled-data tasks
Jason Phang, Thibault Févry, and Samuel R Bowman. 2018 · 2018
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Estimating causal effects of exercise from mood logging data
Dhanya Sridhar, Aaron Springer, Victoria Hollis, Steve Whittaker, and Lise Getoor. 2018 · 2018
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Causality analysis of twitter sentiments and stock market returns
Narges Tabari, Piyusha Biswas, Bhanu Praneeth, Armin Seyeditabari, Mirsad Hadzikadic, and Wlodek Zadrozny. 2018 · 2018
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Challenges of using text classifiers for causal inference
Zach Wood-Doughty, Ilya Shpitser, and Mark Dredze. 2018 · 2018
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Proceedings of the 4th Workshop on Representation Learning for NLP
Isabelle Augenstein, Spandana Gella, Sebastian Ruder, Katharina Kann, Burcu Can, Johannes Welbl, Alexis Conneau, Xiang Ren, and Marek Rei. 2019 · 2019
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Identifying predictive causal factors from news streams
Ananth Balashankar, Sunandan Chakraborty, Samuel Fraiberger, and Lakshminarayanan Subramanian. 2019 · 2019
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Who is the human in human-centered machine learning: The case of predicting mental health from social media
Stevie Chancellor, Eric PS Baumer, and Munmun De Choudhury. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition
Vincent Dorie, Jennifer Hill, Uri Shalit, Marc Scott, and Daniel Cervone. 2019 · 2019
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The case for evaluating causal models using interventional measures and empirical data
Amanda Gentzel, Dan Garant, and David Jensen. 2019 · 2019
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A comparison of approaches to advertising measurement: Evidence from big field experiments at facebook
Brett R Gordon, Florian Zettelmeyer, Neha Bhargava, and Dan Chapsky. 2019 · 2019
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Comment: Strengthening empirical evaluation of causal inference methods
David Jensen. 2019 · 2019
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Identifying when effect restoration will improve estimates of causal effect
Hüseyin Oktay, Akanksha Atrey, and David Jensen. 2019 · 2019
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Sentence-BERT: Sentence embeddings using siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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A social media study on the effects of psychiatric medication use
Koustuv Saha, Benjamin Sugar, John Torous, Bruno Abrahao, Emre Kıcıman, and Munmun De Choudhury. 2019 · 2019
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Estimating causal effects of tone in online debates
Dhanya Sridhar and Lise Getoor. 2019 · 2019
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Causal Inference: What If
MA Hernán and JM Robins. 2020 · 2020
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Matching with text data: An experimental evaluation of methods for matching documents and of measuring match quality
Reagan Mozer, Luke Miratrix, Aaron Russell Kaufman, and L Jason Anastasopoulos. 2020 · 2020
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Adjusting for confounding with text matching
Margaret E Roberts, Brandon M Stewart, and Richard A Nielsen. 2020 · 2020
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Discovering shifts to suicidal ideation from mental health content in social media
Munmun De Choudhury, Emre Kiciman, Mark Dredze, Glen Coppersmith, and Mrinal Kumar. 2016 · 2098
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