| Actionable recourse in linear classification B Ustun, A Spangher, Y Liu Proceedings of the conference on fairness, accountability, and transparency …, 2019 | 610 | 2019 |
| Characterizing the Internet Research Agency’s social media operations during the 2016 US presidential election using linguistic analyses RL Boyd, A Spangher, A Fourney, B Nushi, G Ranade, J Pennebaker, ... PsyArXiv, 2018 | 49 | 2018 |
| Building the next New York Times recommendation engine A Spangher The New York Times, 08-26, 2015 | 40 | 2015 |
| Stay on topic with classifier-free guidance G Sanchez, H Fan, A Spangher, E Levi, PS Ammanamanchi, S Biderman arXiv preprint arXiv:2306.17806, 2023 | 34 | 2023 |
| Analysis of Strategy and Spread of Russia-sponsored Content in the US in 2017 A Spangher, G Ranade, B Nushi, A Fourney, E Horvitz arXiv preprint arXiv:1810.10033, 2018 | 33 | 2018 |
| Multitask semi-supervised learning for class-imbalanced discourse classification A Spangher, J May, SR Shiang, L Deng Proceedings of the 2021 conference on empirical methods in natural language …, 2021 | 32* | 2021 |
| Newsedits: A news article revision dataset and a novel document-level reasoning challenge A Spangher, X Ren, J May, N Peng Proceedings of the 2022 Conference of the North American Chapter of the …, 2022 | 28* | 2022 |
| Actionable recourse in linear classification A Spangher, B Ustun, Y Liu Proceedings of the 5th workshop on fairness, accountability and transparency …, 2018 | 24 | 2018 |
| Understanding multimodal procedural knowledge by sequencing multimodal instructional manuals TL Wu, A Spangher, P Alipoormolabashi, M Freedman, R Weischedel, ... arXiv preprint arXiv:2110.08486, 2021 | 21 | 2021 |
| Enabling low-resource transfer learning across COVID-19 corpora by combining event-extraction and co-training A Spangher, N Peng, J May, E Ferrara Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020, 2020 | 17 | 2020 |
| Sequentially controlled text generation A Spangher, X Hua, Y Ming, N Peng arXiv preprint arXiv:2301.02299, 2023 | 14 | 2023 |
| "Don't quote me on that": Finding Mixtures of Sources in News Articles A Spangher, N Peng, J May, E Ferrara Computation+Journalism2020, arXiv preprint arXiv:2104.09656, 2021 | 9 | 2021 |
| Characterizing search-engine traffic to internet research agency web properties A Spangher, G Ranade, B Nushi, A Fourney, E Horvitz Proceedings of The Web Conference 2020, 2253-2263, 2020 | 8 | 2020 |
| How Does This Article Make You Feel? S Alexander NYT Open, October 31, 2018 | 8 | 2018 |
| Are Large Language Models Capable of Generating Human-Level Narratives? Y Tian, T Huang, M Liu, D Jiang, A Spangher, M Chen, J May, N Peng arXiv preprint arXiv:2407.13248, 2024 | 6 | 2024 |
| Identifying Informational Sources in News Articles A Spangher, N Peng, J May, E Ferrara arXiv preprint arXiv:2305.14904, 2023 | 5 | 2023 |
| Learning action conditions from instructional manuals for instruction understanding TL Wu, C Zhang, Q Hu, A Spangher, N Peng arXiv preprint arXiv:2205.12420, 2022 | 4 | 2022 |
| Do llms plan like human writers? comparing journalist coverage of press releases with llms A Spangher, N Peng, S Gehrmann, M Dredze Proceedings of the 2024 Conference on Empirical Methods in Natural Language …, 2024 | 3 | 2024 |
| what’s the diff?”: Examining news article updates and changing narratives during the uss theodore roosevelt coronavirus crisis A Spangher, AL Scott, K Huang-Isherwood Annenberg Scymposium, 2021 | 3 | 2021 |
| If it bleeds, it leads: A computational approach to covering crime in los angeles A Spangher, D Choudhary arXiv preprint arXiv:2206.07115, 2022 | 2 | 2022 |
