Publications

Protecting Information Integrity

Publications

Chen, B., Lukito, J., & Koo, G. H. (2023). Comparing the #StopTheSteal Movement across Multiple Platforms: Differentiating Discourse on Facebook, Twitter, and Parler. Social Media + Society 9 (3) , 20563051231196879 . https://doi.org/10.1177/20563051231196879

Chen, B., Murthy, D., Kim, T. (., Kolluri, N., Won, C., Venkatesh, P., & Lukito, J. (2022). Beyond Racism: Examining interaction between racist speech and misinformation on Parler.

Chen, J., Kim, G., Sriram, A., Durrett, G., & Choi, E. (2024). Complex Claim Verification with Evidence Retrieved in the Wild. 3569-3587 . https://doi.org/10.18653/v1/2024.naacl-long.196

Chen, J., Sriram, A., Choi, E., & Durrett, G. (2022). Generating Literal and Implied Subquestions to Fact-check Complex Claims. 3495-3516 . https://doi.org/10.18653/v1/2022.emnlp-main.229

Cheng, M., De-Arteaga, M., Mackey, L., & Kalai, A. T. (2023). Social norm bias: residual harms of fairness-aware algorithms. Data Mining and Knowledge Discovery . https://doi.org/10.1007/s10618-022-00910-8

Das, A., Gupta, C., Kovatchev, V., Lease, M., & Li, J. J. (2022). ProtoTEx: Explaining Model Decisions with Prototype Tensors. http://arxiv.org/abs/2204.05426

Das, A., Liu, H., Kovatchev, V., & Lease, M. (2022). The Need for Human-centered Design in Fact-Checking Research. https://utexas.app.box.com/v/das-ipmc2022

Das, A., Liu, H., Kovatchev, V., & Lease, M. (2023). The state of human-centered NLP technology for fact-checking. Information Processing & Management 60 (2) , 103219 . https://doi.org/10.1016/j.ipm.2022.103219

De-Arteaga, M., Jeanselme, V., Dubrawski, A., & Chouldechova, A. (2025). Leveraging Expert Consistency to Improve Algorithmic Decision Support. Management Science mnsc.2022.01576 . https://doi.org/10.1287/mnsc.2022.01576

Deck, L., Schoeffer, J., De-Arteaga, M., & Kühl, N. (2024). A Critical Survey on Fairness Benefits of Explainable AI. 1579-1595 . https://doi.org/10.1145/3630106.3658990

De‐Arteaga, M., Feuerriegel, S., & Saar‐Tsechansky, M. (2022). Algorithmic fairness in business analytics: Directions for research and practice. Production and Operations Management 31 (10) , 3749-3770 . https://doi.org/10.1111/poms.13839

Dhiraj, M., Dasari, T., Vinton, K., Lago Arroyo, F., Li, C., & Clayton, P. (2023). Using Machine Learning, Social Media Images, and Journalists to Improve Disaster Resilience and Response. SSRN Electronic Journal . https://doi.org/10.2139/ssrn.4326541

Fazelpour, S., & De-Arteaga, M. (2022). Diversity in sociotechnical machine learning systems. Big Data & Society 9 (1) , 205395172210820 . https://doi.org/10.1177/20539517221082027

Gao, R., Saar-Tsechansky, M., De-Arteaga, M., Han, L., Sun, W., Lee, M. K., & Lease, M. (2023). Learning Complementary Policies for Human-AI Teams. https://doi.org/10.48550/ARXIV.2302.02944

Goodwin, A., Joseff, K., Riedl, M. J., Lukito, J., & Woolley, S. Political Relational Influencers: The Mobilization of Social Media Influencers in the Political Arena. International Journal of Communication 17 . https://ijoc.org/index.php/ijoc/article/view/18987

Govindarajan, V. S., Atwell, K., Sinno, B., Alikhani, M., Beaver, D. I., & Li, J. J. (2023). How people talk about each other: Modeling Generalized Intergroup Bias and Emotion. 2496-2506 . https://doi.org/10.18653/v1/2023.eacl-main.183

Govindarajan, V. S., Beaver, D., Mahowald, K., & Li, J. J. (2023). Counterfactual Probing for the Influence of Affect and Specificity on Intergroup Bias. 12853-12862 . https://doi.org/10.18653/v1/2023.findings-acl.813

Gupta, S., Kovatchev, V., Das, A., De-Arteaga, M., & Lease, M. (2025). Finding Pareto trade-offs in fair and accurate detection of toxic speech. Information Research an international electronic journal 30 (iConf) , 123-141 . https://doi.org/10.47989/ir30iconf47572

Gupta, S., Lee, S., De-Arteaga, M., & Lease, M. (2023). Same Same, But Different: Conditional Multi-Task Learning for Demographic-Specific Toxicity Detection. 3689-3700 . https://doi.org/10.1145/3543507.3583290

Hettiachchi, D., Holcombe-James, I., Livingstone, S., De Silva, A., Lease, M., Salim, F. D., & Sanderson, M. (2023). How Crowd Worker Factors Influence Subjective Annotations: A Study of Tagging Misogynistic Hate Speech in Tweets. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 11 (1) , 38-50 . https://doi.org/10.1609/hcomp.v11i1.27546

Holstein, K., De-Arteaga, M., Tumati, L., & Cheng, Y. (2023). Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables. Proceedings of the ACM on Human-Computer Interaction 7 (CSCW1) , 1-20 . https://doi.org/10.1145/3579628

Jeanselme, V., De-Arteaga, M., Zhang, Z., Barrett, J., & Tom, B. (2022). Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness. 193 , 12-34 . https://doi.org/10.48550/ARXIV.2208.06648

Jia, C., Boltz, A., Zhang, A., Chen, A., & Lee, M. K. (2022). Understanding Effects of Algorithmic vs. Community Label on Perceived Accuracy of Hyper-partisan Misinformation. Proceedings of the ACM on Human-Computer Interaction 6 (CSCW2) , 1-27 . https://doi.org/10.1145/3555096

Joseph, S. A., Chen, L., Trienes, J., Göke, H. L., Coers, M., Xu, W., Wallace, B. C., & Li, J. J. (2024). FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence. http://arxiv.org/abs/2402.11456

Kambhatla, G., Lease, M., & Rajadesingan, A. (2024). Promoting Constructive Deliberation: Reframing for Receptiveness. 5110-5132 . https://doi.org/10.18653/v1/2024.findings-emnlp.294

Kamoi, R., Goyal, T., & Durrett, G. (2023). Shortcomings of Question Answering Based Factuality Frameworks for Error Localization. https://doi.org/10.48550/ARXIV.2210.06748

Kamoi, R., Goyal, T., Rodriguez, J. D., & Durrett, G. (2023). WiCE: Real-World Entailment for Claims in Wikipedia. http://arxiv.org/abs/2303.01432

Kolluri, A., Murthy, D., & Vinton, K. (2025). Quantifying the spread of racist content on fringe social media: A case study of Parler. Big Data & Society 12 (2) , 20539517251321752 . https://doi.org/10.1177/20539517251321752

Kolluri, N. L., & Murthy, D. (2021). CoVerifi: A COVID-19 news verification system. Online Social Networks and Media 22 , 100123 . https://doi.org/10.1016/j.osnem.2021.100123

Kolluri, N. L., Liu, Y., & Murthy, D. (2022). COVID-19 Misinformation Detection: Machine Learned Solutions to the Infodemic (Preprint). JMIR Infodemiology . https://doi.org/10.2196/38756

Kovatchev, V., Chatterjee, T., Govindarajan, V. S., Chen, J., Choi, E., Chronis, G., Das, A., Erk, K., Lease, M., Li, J. J., Wu, Y., & Mahowald, K. (2022). longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks.. 41-52 . https://doi.org/10.18653/v1/2022.dadc-1.5

Lee, T., & Koo, G. H. (2022). What Drives Belief in COVID-19 Conspiracy Theories? Examining the Role of Uncertainty, Negative Emotions, and Perceived Relevance and Threat. Health Communication 1-11 . https://doi.org/10.1080/10410236.2022.2134703

Li, Y., De-Arteaga, M., & Saar-Tsechansky, M. (2023). Mitigating Label Bias via Decoupled Confident Learning. http://arxiv.org/abs/2307.08945

Li, Y., De-Arteaga, M., & Saar-Tsechansky, M. (2022). More Data Can Lead Us Astray: Active Data Acquisition in the Presence of Label Bias. https://doi.org/10.48550/ARXIV.2207.07723

Liu, H., Das, A., Boltz, A., Zhou, D., Pinaroc, D., Lease, M., & Lee, M. K. (2024). Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AI. Proceedings of the ACM on Human-Computer Interaction 8 (CSCW2) , 1-44 . https://doi.org/10.1145/3686962

Liu, H., Gwizdka, J., & Lease, M. (2025). Exploring Multidimensional Checkworthiness: Designing AI-assisted Claim Prioritization for Human Fact-checkers. https://doi.org/10.48550/ARXIV.2412.08185

Lukito, J. (2023). Digital Disinformation, Electoral Interference, and Systemic Distrust. In Routledge Handbook of Disinformation and National Security. Routledge. https://www.routledge.com/Routledge-Handbook-of-Disinformation-and-National-Security/Arcos-Chiru-Ivan/p/book/9781032040509

Lukito, J. (2024). Global Misinformation & Disinformation Special Issue Introduction. International Journal of Public Opinion Research 36 (3) , edae030 . https://doi.org/10.1093/ijpor/edae030

Lukito, J. (2024). Understanding a Case of State-Sponsored Digital Disinformation. In The Disinformers: Social Media, Disinformation, and Elections. LSU Press. https://muse.jhu.edu/pub/236/edited_volume/chapter/3962512#info_wrap

Lukito, J., Cui, Z., Hu, A., Lee, T., & Ozawa, J. V. S. (2022). States vs. Social Movements: Protests and State Repression in Asia. Media and Communication 10 (4) . https://doi.org/10.17645/mac.v10i4.5623

Lukito, J., Greenfield, J., Yang, Y., Dahlke, R., Brown, M. A., Lewis, R., & Chen, B. (2024). Audio-as-Data Tools: Replicating Computational Data Processing. Media and Communication 12 , 7851 . https://doi.org/10.17645/mac.7851

Lukito, J., Gursky, J., Foley, J., Yang, Y., Joseff, K., & Borah, P. (2023). “No Reason[.] [I]t /Should/ Happen here”: Analyzing Flynn’s Retroactive Doublespeak During a QAnon Event. Political Communication 40 (5) , 576-595 . https://doi.org/10.1080/10584609.2023.2185332

Lukito, J., Lee, T., Martin, Z., Glover, K., Hu, A., & Cui, Z. (2023). Connective action in Myanmar: a mixed-method analysis of Spring Revolution. Information, Communication & Society 1-19 . https://doi.org/10.1080/1369118X.2023.2289973

Lukito, J., Macdonald, M., Chen, B., Brown, M. A., Prochaska, S., Yang, Y., Greenfield, J., Suk, J., Zhong, W., Dahlke, R., & Borah, P. (2025). Candidates Be Posting: Multi-Platform Strategies and Partisan Preferences in the 2022 U.S. Midterm Elections. Social Media + Society 11 (2) , 20563051251337541 . https://doi.org/10.1177/20563051251337541

Murthy, D. (2023). “They’re Coming to Take over Our Country”: Researching Global Circuits of Racist Misinformation. Social Science Research Council, MediaWell . https://mediawell.ssrc.org/articles/theyre-coming-to-take-over-our-country-researching-global-circuits-of-racist-misinformation/

Neumann, T., De-Arteaga, M., & Fazelpour, S. (2022). Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harms. 1504-1515 . https://doi.org/10.1145/3531146.3533205

Ozawa, J. V. S., Lukito, J., Lee, T., Varma, A., & Alves, R. (2023). Attacks Against Journalists in Brazil: Catalyzing Effects and Resilience During Jair Bolsonaro’s Government. The International Journal of Press/Politics 19401612231182618 . https://doi.org/10.1177/19401612231182618

Pradhan, V. K., Schaekermann, M., & Lease, M. (2022). In Search of Ambiguity: A Three-Stage Workflow Design to Clarify Annotation Guidelines for Crowd Workers. Frontiers in Artificial Intelligence 5 , 828187 . https://doi.org/10.3389/frai.2022.828187

Rodarte, A. K., & Lukito, J. (2025). Does Social Media Level the Political Field or Reinforce Existing Inequalities? Cartographies of the 2022 Brazilian Election. Political Communication 42 (3) , 382-404 . https://doi.org/10.1080/10584609.2024.2439320

Rodarte, A. K., Hyunsik Kim, T., & Lukito, J. (2023). Representing “The People”: What Can Social Media Images Reveal About Populist Propaganda in Brazil?. Social Media + Society 9 (2) , 20563051231177962 . https://doi.org/10.1177/20563051231177962

Schoeffer, J., De-Arteaga, M., & Elmer, J. (2025). Perils of Label Indeterminacy: A Case Study on Prediction of Neurological Recovery After Cardiac Arrest. https://doi.org/https://facctconference.org/static/docs/facct2025-206archivalpdfs/facct2025-final355-acmpaginated.pdf

Schoeffer, J., De-Arteaga, M., & Kuehl, N. (2022). On the Relationship Between Explanations, Fairness Perceptions, and Decisions. http://arxiv.org/abs/2204.13156

Schoeffer, J., De-Arteaga, M., & Kühl, N. (2024). Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making. 1-18 . https://doi.org/10.1145/3613904.3642621

Shi, L., Bhattacharya, N., Das, A., Lease, M., & Gwizdka, J. (2022). The Effects of Interactive AI Design on User Behavior: An Eye-tracking Study of Fact-checking COVID-19 Claims. 315-320 . https://doi.org/10.1145/3498366.3505786

Singh, S., Caragea, C., & Li, J. J. (2023). Language Models (Mostly) Do Not Consider Emotion Triggers When Predicting Emotion. https://doi.org/10.48550/ARXIV.2311.09602

Sinno, B., Oviedo, B., Atwell, K., Alikhani, M., & Li, J. J. (2022). Political Ideology and Polarization: A Multi-dimensional Approach. 231-243 . https://doi.org/10.18653/v1/2022.naacl-main.17

Sosea, T., Pham, C., Tekle, A., Caragea, C., & Li, J. J. (2022). Emotion analysis and detection during COVID-19. 6938-6947 . https://doi.org/10.48550/ARXIV.2107.11020

Su, Y., Li, J. J., & Lease, M. (2024). Wrapper Boxes for Faithful Attribution of Model Predictions to Training Data. 551-576 . https://doi.org/10.18653/v1/2024.blackboxnlp-1.33

Tang, L., Laban, P., & Durrett, G. (2024). MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents. 8818-8847 . https://doi.org/10.18653/v1/2024.emnlp-main.499

Trienes, J., Joseph, S., Schlötterer, J., Seifert, C., Lo, K., Xu, W., Wallace, B. C., & Li, J. J. (2024). InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification. http://arxiv.org/abs/2401.16475

Verma, N., Fleischmann, K. R., Zhou, L., Xie, B., Lee, M. K., Rich, K., Shiroma, K., Jia, C., & Zimmerman, T. (2022). Trust in COVID ‐19 public health information. Journal of the Association for Information Science and Technology asi.24712 . https://doi.org/10.1002/asi.24712

Wu, Y., Mangla, R. R., Dimakis, A., Durrett, G., & Li, J. J. (2024). Which questions should I answer? Salience Prediction of Inquisitive Questions. 19969-19987 . https://doi.org/10.18653/v1/2024.emnlp-main.1114

Zhang, A., Boltz, A., Lynn, J., Wang, C. W., & Lee, M. K. (2023). Stakeholder-Centered AI Design: Co-Designing Worker Tools with Gig Workers through Data Probes. 1-19 . https://doi.org/10.1145/3544548.3581354

Zhang, A., Walker, O., Nguyen, K., Dai, J., Chen, A., & Lee, M. K. (2023). Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7 (CSCW1) , 1-32 . https://doi.org/10.1145/3579601

Zhang, Y., Chen, F., & Lukito, J. (2023). Network Amplification of Politicized Information and Misinformation about COVID-19 by Conservative Media and Partisan Influencers on Twitter. Political Communication 40 (1) , 24-47 . https://doi.org/10.1080/10584609.2022.2113844

Zhang, Y., Lukito, J., Suk, J., & McGrady, R. (2024). Trump, Twitter, and Truth Social: how Trump used both mainstream and alt-tech social media to drive news media attention. Journal of Information Technology & Politics 1-14 . https://doi.org/10.1080/19331681.2024.2328156

Zimmerman, T., Shiroma, K., Fleischmann, K. R., Xie, B., Jia, C., Verma, N., & Lee, M. K. (2023). Misinformation and COVID-19 vaccine hesitancy. Vaccine 41 (1) , 136-144 . https://doi.org/10.1016/j.vaccine.2022.11.014