| Gender identity and lexical variation in social media D Bamman, J Eisenstein, T Schnoebelen Journal of Sociolinguistics 18 (2), 135-160, 2014 | 695 | 2014 |
| Gender and representation bias in GPT-3 generated stories L Lucy, D Bamman Proceedings of the third workshop on narrative understanding, 48-55, 2021 | 552 | 2021 |
| Contextualized sarcasm detection on twitter D Bamman, N Smith proceedings of the international AAAI conference on web and social media 9 …, 2015 | 546 | 2015 |
| Censorship and deletion practices in Chinese social media D Bamman, B O'Connor, N Smith First Monday, 2012 | 516 | 2012 |
| Learning Latent Personas of Film Characters D Bamman, B O'Connor, N Smith ACL, 2013 | 365 | 2013 |
| A Bayesian Mixed Effects Model of Literary Character D Bamman, T Underwood, NA Smith ACL, 2014 | 315 | 2014 |
| Adversarial training for relation extraction Y Wu, D Bamman, S Russell Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 278 | 2017 |
| Speak, memory: An archaeology of books known to chatgpt/gpt-4 K Chang, M Cramer, S Soni, D Bamman Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 218 | 2023 |
| The transformation of gender in English-language fiction T Underwood, D Bamman, S Lee Journal of Cultural Analytics 3 (2), 2018 | 175 | 2018 |
| The ancient Greek and Latin dependency treebanks D Bamman, G Crane Language technology for cultural heritage: Selected papers from the LaTeCH …, 2011 | 174 | 2011 |
| Narrative theory for computational narrative understanding A Piper, RJ So, D Bamman Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 173 | 2021 |
| An annotated dataset of coreference in English literature D Bamman, O Lewke, A Mansoor Proceedings of the Twelfth Language Resources and Evaluation Conference, 44-54, 2020 | 169 | 2020 |
| Learning to groove with inverse sequence transformations J Gillick, A Roberts, J Engel, D Eck, D Bamman International conference on machine learning, 2269-2279, 2019 | 153 | 2019 |
| An annotated dataset of literary entities D Bamman, S Popat, S Shen Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 146 | 2019 |
| Distributed Representations of Geographically Situated Language D Bamman, C Dyer, NA Smith ACL, 2014 | 146 | 2014 |
| Literary event detection M Sims, JH Park, D Bamman Proceedings of the 57th annual meeting of the association for computational …, 2019 | 136 | 2019 |
| Latin bert: A contextual language model for classical philology D Bamman, PJ Burns arXiv preprint arXiv:2009.10053, 2020 | 128 | 2020 |
| The design and use of a Latin dependency treebank D Bamman, G Crane Proceedings of the Fifth Workshop on Treebanks and Linguistic Theories …, 2006 | 100 | 2006 |
| Computational text analysis for social science: Model assumptions and complexity B O’Connor, D Bamman, NA Smith NIPS Workshop on Computational Social Science and the Wisdom of Crowds, 2011 | 95 | 2011 |
| Unsupervised Discovery of Biographical Structure from Text D Bamman, NA Smith TACL, 2014 | 92 | 2014 |
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
