aron culotta       
associate professor of computer science
director - center for community-engaged artificial intelligence
tulane university

cv   scholar   teaching   funding   awards   pubs

I investigate computational methods to discover socially-beneficial knowledge from text and social networks. Examples include tracking diseases, measuring effectiveness of public health campaigns, informing crisis response, preventing online harassment, detecting deceptive marketing, and identifying unsafe products.

The methods rely on machine learning, natural language processing, and social network analysis. Areas of technical contribution include domain adaptation, learning from label proportions, and causal inference.

I also lead the Tulane Center for Community-Engaged Artificial Intelligence and the Jurist Center for Artificial Intelligence.

Are you a student interested in a phd or independent study?


natural language processing        intro to algorithms        intro to data science
artificial intelligence        online social network analysis        information retrieval


This research is made possible in part by the National Science Foundation, the Jurist Center for Artificial Intelligence, the Newcomb Institute, Tulane's Office of Research, the Nayar Prize, and the Educational and Research Initiative. I am grateful for this support.



Use Open Source for Safer Generative AI Experiments
Aron Culotta, Nicholas Mattei
MIT Sloan Management Review, 2023
Domain Adaptation for Learning from Label Proportions Using Domain-Adversarial Neural Network
Xintian Li, Aron Culotta
SN Computer Science, 2023
Online Reviews Are Leading Indicators of Changes in K-12 School Attributes
Linsen Li, Aron Culotta, Douglas N. Harris, Nicholas Mattei
WWW, 2023
Forecasting COVID-19 Vaccination Rates using Social Media Data
Xintian Li, Aron Culotta
SocialNLP, 2023
Safety Reviews on Airbnb: An Information Tale
Aron Culotta, Ginger Zhe Jin, Yidan Sun, Liad Wagman
PlatStrat, 2022
Reducing Cross-Topic Political Homogenization in Content-Based News Recommendation
Karthik Shivaram, Ping Liu, Matthew Shapiro, Mustafa Bilgic, Aron Culotta
RecSys, 2022
Identifying Hurricane Evacuation Intent on Twitter
Xintian Li, Samiul Hasan, Aron Culotta
ICWSM, 2022
Leaders or Followers? A Temporal Analysis of Tweets from IRA Trolls
Siva K Balasubramanian, Mustafa Bilgic, Aron Culotta, Libby Hemphill, Libby, Anita Nikolich, Matthew A Shapiro
ICWSM, 2022
Enhancing Model Robustness and Fairness with Causality: A Regularization Approach
Zhao Wang, Kai Shu, and Aron Culotta
EMNLP WS, 2021
The Interaction between Political Typology and Filter Bubbles in News Recommendation Algorithms
Ping Liu, Karthik Shivaram, Matthew Shapiro, Aron Culotta, Mustafa Bilgic
WWW, 2021
Robustness to Spurious Correlations in Text Classification via Automatically Generated Counterfactuals
Zhao Wang, Aron Culotta
AAAI, 2021
Identifying Spurious Correlations for Robust Text Classification
Zhao Wang, Aron Culotta
EMNLP, 2020
Characterizing Variation in Toxic Language by Social Context
Bahar Radfar, Karthik Shivaram, Aron Culotta
ICWSM, 2020
Big data and emergency management: Concepts, methodologies, and applications
Xuan Song, Haoran Zhang, Rajendra A. Akerkar, Huawei Huang, Song Guo, Lei Zhong, Yusheng Ji, Andreas Lothe Opdahl, Hemant Purohit, Andre Supkin, Akshay Pottathil, Aron Culotta
IEEE BigData, 2020
When do words matter? Understanding the Impact of Lexical Choice on Audience Perception using Individual Treatment Effect Estimation
Zhao Wang, Aron Culotta
AAAI, 2019
Discovering and Controlling for Latent Confounds in Text Classification Using Adversarial Domain Adaptation
Virgile Landeiro, Tuan Tran, Aron Culotta
SDM, 2019
Using weak supervision to scale the development of machine-learning models for social media-based marketing research
Jennifer Cutler, Aron Culotta
Applied Marketing Analytics, 2019
Collecting Representative Samples from a Search Engine by Adaptive Query Generation
Virgile Landeiro, Aron Culotta
ASONAM, 2019
Estimating Tie Strength in Follower Networks to Measure Brand Perceptions
Tung Nguyen, Li Zhang, Aron Culotta
FAB, 2019
Personality and Behavior in Role-based Online Games
Zhao Wang, Anna Sapienza, Aron Culotta, Emilio Ferrara
COG, 2019
Robust Text Classification under Confounding Shift
Virgile Landeiro, Aron Culotta
JAIR, 2018
Forecasting the presence and intensity of hostility on Instagram using linguistic and social features
Ping Liu, Joshua Guberman, Libby Hemphill, Aron Culotta
ICWSM, 2018
Learning from noisy label proportions for classifying online social data
Ehsan Mohammady Ardehaly, Aron Culotta
SNAM, 2018
Mining the Demographics of Political Sentiment from Twitter Using Learning from Label Proportions
Ehsan Ardehaly, Aron Culotta
ICDM, 2017
Co-training for Demographic Classification Using Deep Learning from Label Proportions
Ehsan Ardehaly, Aron Culotta
ICDM-WS, 2017
Are Words Commensurate with Actions? Quantifying Commitment to a Cause from Online Public Messaging
Zhao Wang, Jennifer Cutler, Aron Culotta
ICDM-WS, 2017
Controlling for Unobserved Confounds in Classification Using Correlational Constraints
Virgile Landeiro, Aron Culotta
ICWSM, 2017
Identifying leading indicators of product recalls from online reviews using positive unlabeled learning and domain adaptation
Shreesh Kumara Bhat, Aron Culotta
ICWSM, 2017
Using online social networks to measure consumers’ brand perception
Jennifer Cutler, Aron Culotta
Applied Marketing Analytics, 2017
Towards identifying leading indicators of smoking cessation attempts from social media
Aron Culotta
ICHI-WS, 2016
Polar Scores: Measuring Partisanship Using Social Media Content
Libby Hemphill, Aron Culotta, Matthew Heston
Journal of Information Technology & Politics, 2016
Cold-start recommendations for audio news stories using matrix factorization
Ehsan Mohammady Ardehaly, Aron Culotta
IJCAI, 2016
Domain adaptation for learning from label proportions using self-training
Ehsan Mohammady Ardehaly, Aron Culotta
IJCAI, 2016
Training a text classifier with a single word using Twitter Lists and domain adaptation
Aron Culotta
SNAM, 2016
Reducing confounding bias in observational studies that use text classification
Virgile Landeiro, Aron Culotta
AAAI Symposium, 2016
Predicting Twitter User Demographics using Distant Supervision from Website Traffic Data
Aron Culotta, Nirmal Kumar Ravi, Jennifer Cutler
JAIR, 2016
Mining brand perceptions from Twitter social networks
Aron Culotta, Jennifer Cutler
Marketing Science, 2016
Robust text classification in the presence of confounding variables
Virgile Landeiro, Aron Culotta
AAAI, 2016
Finding truth in cause-related advertising: A lexical analysis of brands' health, environment, and social justice communications on Twitter
Aron Culotta, Jennifer Cutler, Junzhe Zheng
The Journal of Values-Based Leadership, 2015
A demographic and sentiment analysis of e-cigarette messages on Twitter
Elaine Cristina Resende, Aron Culotta
BCB-WS, 2015
Inferring latent attributes of Twitter users with label regularization
Ehsan Mohammady Ardehaly, Aron Culotta
Using Matched Samples to Estimate the Effects of Exercise on Mental Health from Twitter
Virgile Landeiro Dos Reis, Aron Culotta
AAAI, 2015
Predicting the Demographics of Twitter Users from Website Traffic Data
Aron Culotta, Nirmal Ravi Kumar, Jennifer Cutler
AAAI, 2015
Reducing Sampling Bias in Social Media Data for County Health Inference
Aron Culotta
JSM, 2014
Anytime Active Learning
Maria E Ramirez-Loaiza, Aron Culotta, Mustafa Bilgic
AAAI, 2014
Using county demographics to infer attributes of Twitter users
Ehsan Mohammady, Aron Culotta
ACL-WS, 2014
Tweedr: Mining Twitter to Inform Disaster Response
Zahra Ashktorab, Christopher Brown, Manojit Nandi, Aron Culotta
ISCRAM, 2014
Estimating County Health Statistics with Twitter
Aron Culotta
CHI, 2014
Inferring the origin location of tweets with quantitative confidence
Reid Priedhorsky, Aron Culotta, Sara Y. Del Valle
CSCW, 2014
Lightweight methods to estimate influenza rates and alcohol sales volume from Twitter messages
Aron Culotta
LREC, 2013
Framing in Social Media: How the US Congress Uses Twitter Hashtags to Frame Political Issues
Libby Hemphill, Aron Culotta, Matthew Heston
Tech Report, 2013
Towards Anytime Active Learning: Interrupting Experts to Reduce Annotation Costs
Maria E. Ramirez-Loaiza, Aron Culotta, Mustafa Bilgic
KDD-WS, 2013
Too Neurotic, Not too Friendly: Structured Personality Classification on Textual Data
Francisco Iacobelli, Aron Culotta
ICWSM-WS, 2013
A demographic analysis of online sentiment during Hurricane Irene
Benjamin Mandel, Aron Culotta, John Boulahanis, Danielle Stark, Bonnie Lewis, Jeremy Rodrigue
SampleRank: Training factor graphs with atomic gradients
Michael Wick, Khashayar Rohanimanesh, Kedar Bellare, Aron Culotta, Andrew McCallum
ICML, 2011
Detecting influenza epidemics by analyzing Twitter messages
Aron Culotta
Tech Report, 2010
Towards detecting influenza epidemics by analyzing Twitter messages
Aron Culotta
KDD-WS, 2010
SampleRank: Learning preferences from atomic gradients
Michael Wick, Khashayar Rohanimanesh, Aron Culotta, Andrew McCallum
NIPS-WS, 2009
An entity-based model for coreference resolution
Michael Wick, Aron Culotta, Khashayar Rohanimanesh, Andrew McCallum
SDM, 2009
Learning and inference in weighted logic with application to natural language processing
Aron Culotta
PhD Thesis, 2008
Canonicalization of Database Records using Adaptive Similarity Measures
Aron Culotta, Michael Wick, Robert Hall, Matthew Marzilli, Andrew McCallum
KDD, 2007
Sparse Message Passing Algorithms for Weighted Maximum Satisfiability
Aron Culotta, Andrew McCallum, Bart Selman, Ashish Sabharwal
NESCAI, 2007
Author Disambiguation using Error-driven Machine Learning with a Ranking Loss Function
Aron Culotta, Pallika Kanani, Robert Hall, Michael Wick, Andrew McCallum
IIWeb, 2007
First-Order Probabilistic Models for Coreference Resolution
Aron Culotta, Michael Wick, Robert Hall, Andrew McCallum
Corrective Feedback and Persistent Learning for Information Extraction
Aron Culotta, Trausti Kristjansson, Andrew McCallum, Paul Viola
Artificial Intelligence, 2006
Tractable Learning and Inference with High-Order Representations
Aron Culotta, Andrew McCallum
ICML-WS, 2006
Learning field compatibilities to extract database records from unstructured text
Michael Wick, Aron Culotta, Andrew McCallum
EMNLP, 2006
Practical Markov logic containing first-order quantifiers with application to identity uncertainty
Aron Culotta, Andrew McCallum
Integrating probabilistic extraction models and data mining to discover relations and patterns in text
Aron Culotta, Andrew McCallum, Jonathan Betz
Learning clusterwise similarity with first-order features
Aron Culotta, Andrew McCallum
NIPS-WS, 2005
A conditional model of deduplication for multi-type relational data
Aron Culotta, Andrew McCallum
Tech Report, 2005
Joint deduplication of multiple record types in relational data
Aron Culotta, Andrew McCallum
CIKM, 2005
Reducing labeling effort for structured prediction tasks
Aron Culotta, Andrew McCallum
AAAI, 2005
Gene prediction with conditional random fields
Aron Culotta, David Kulp, Andrew McCallum
Tech Report, 2005
Dependency tree kernels for relation extraction
Aron Culotta, Jeffery Sorensen
ACL, 2004
Interactive information extraction with constrained conditional random fields
Trausti Kristjannson, Aron Culotta, Paul Viola, Andrew McCallum
AAAI, 2004
Confidence estimation for information extraction
Aron Culotta, Andrew McCallum
HLT, 2004
Extracting social networks and contact information from email and the Web
Aron Culotta, Ron Bekkerman, Andrew McCallum
CEAS, 2004
Maximizing cascades in social networks
Aron Culotta
Tech Report, 2003