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Can Large Language Models Transform Computational Social Science?

Written for the Research library (claude-opus-5-5) from the paper text, in our own words: the license "arXiv — non-exclusive license to distribute" does not allow redistributing the text itself. Original — arxiv.org/pdf/2305.03514

Summary

Computational Social Science (CSS) usually depends on supervised classifiers, which need large hand-labeled datasets, or on unsupervised methods, whose outputs are often hard to interpret. The authors test whether zero-shot prompting of large language models can remove this bottleneck. They reviewed CSS and digital-humanities research across history, literature, linguistics, political science, psychology and sociology. From that review they built a benchmark of English tasks at the utterance, conversation and document level. The abstract counts 25 tasks and the body text counts 24. They then evaluated 13 open and closed models zero-shot, using a set of prompting guidelines, and compared them with fine-tuned baselines. On labeling tasks, the LLMs rarely beat well-tuned supervised models and are not accurate enough to replace annotators, although their agreement with human labels is moderate. On generative tasks, such as explaining figurative language or hateful content, the strongest models write explanations as good as or better than crowdsourced references. The study gives social scientists a practical guide: treat LLMs as an extra annotator alongside humans and as a starting point for explanation-style coding, not as a full replacement for human work.

Key points

  • Evaluation setup: 13 language models of different sizes, pretraining and instruction-tuning types were tested with zero-shot prompts on about two dozen English CSS datasets. Topics include ideology, stance, event extraction, emotion, humor, politeness, toxicity, misinformation and positive reframing.
  • Classification: Prompted models generally trail fine-tuned classifiers, but their agreement with human annotators is fair, and the results improve as models get larger.
  • Generation: For free-text explanations, human judges preferred model outputs about half the time. Top models scored above the gold references on relevance, coherence, faithfulness and fluency.
  • Recommended uses: (1) A zero-shot annotator inside a joint human-AI labeling loop; (2) bootstrapping hard creative coding tasks, such as explaining the hidden attributes of a text.
  • Limitations noted: The data is only English and comes mostly from WEIRD populations. Test sets may have leaked into pretraining data. The study could not systematically analyze social bias. Proprietary APIs carry privacy and copyright risks. LLMs are not reliable for causal explanations.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Other

Cited by

216 papers of our library cite it (of the 140673 whose bibliographies we read); 7 of them have a page here, 209 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.48550/arxiv.2305.03514 · arXiv 2305.03514

@misc{ziems2023can,
  title = {{Can Large Language Models Transform Computational Social Science?}},
  author = {Ziems, Caleb and Held, William and Shaikh, Omar and Chen, Jiaao and Zhang, Zhehao and Yang, Diyi},
  year = {2023},
  doi = {10.48550/arxiv.2305.03514},
  eprint = {2305.03514},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.2305.03514}
}

References

312 references, 38 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Abbott, Andrew. 1990. Conceptions of time and events in social science methods: Causal and narrative approaches. Historical Methods: A Journal of Quantitative and Interdisciplinary History, 23(4):140–150. find
  2. Abid, Abubakar, Maheen Farooqi, and James Zou. 2021. Persistent anti-muslim bias in large language models. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, pages 298–306. find our card
  3. Abul-Fottouh, Deena and Tina Fetner. 2018. Solidarity or schism: ideological Volume 50, Number 1 congruence and the twitter networks of egyptian activists. Mobilization: An International Quarterly, 23(1):23–44. find
  4. Ahmed, Amr and Eric Xing. 2010. Staying informed: Supervised and semi-supervised multi-view topical analysis of ideological perspective. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 1140–1150, Association for Computational Linguistics, Cambridge, M… find
  5. Ziems, Held, Shaikh, Chen, Zhang, Yang Ahuja, Ojas, Jiacheng Xu, Akshay Gupta, Kevin Horecka, and Greg Durrett. 2022. Aspectnews: Aspect-oriented summarization of news documents. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages… find
  6. Althoff, Tim, Cristian Danescu-Niculescu-Mizil, and Dan Jurafsky. 2014. How to ask for a favor: A case study on the success of altruistic requests. In Proceedings of the International AAAI Conference on Web and Social Media, volume 8, pages 12–21. find
  7. Altikriti, Sahar. 2016. Persuasive speech acts in barack obama’s inaugural speeches (2009, 2013) and the last state of the union address (2016). International Journal of Linguistics, 8(2):47–66. find
  8. Amber, Boydstun, Gross Justin, Philip Resnik, and Noah Smith. 2013. Identifying media frames and frame dynamics within and across policy issues. In New directions in analyzing text as Data workshop. find
  9. Anderson, Cameron, Oliver P John, Dacher Keltner, and Ann M Kring. 2001. Who attains social status? effects of personality and physical attractiveness in social groups. Journal of personality and social psychology, 81(1):116. find
  10. Andersson, Lynne M and Christine M Pearson. 1999. Tit for tat? the spiraling effect of incivility in the workplace. Academy of management review, 24(3):452–471. find
  11. Argyle, Lisa P, Ethan C Busby, Nancy Fulda, Joshua R Gubler, Christopher Rytting, and David Wingate. 2022. Out of one, many: Using language models to simulate human samples. Political Analysis, pages 1–15. find our card
  12. Bail, Chris. 2014. Terrified: How anti-Muslim fringe organizations became mainstream. Princeton University Press. find
  13. Bail, Christopher A. 2016. Emotional feedback and the viral spread of social media messages about autism spectrum disorders. American journal of public health, 106(7):1173–1180. find
  14. Bail, Christopher A. 2023. Can generative ai improve social science? find
  15. Bakhtin, Mikhail Mikhaı̆lovich. 2010. Speech genres and other late essays. University of Texas press. find
  16. Baly, Ramy, Giovanni Da San Martino, James Glass, and Preslav Nakov. 2020. We can detect your bias: Predicting the political ideology of news articles. In Proceedings of the 2020 Conference on Empirical Methods in Can LLMs Transform CSS? find
  17. Natural Language Processing (EMNLP), pages 4982–4991, Association for Computational Linguistics, Online. find
  18. Baly, Ramy, Georgi Karadzhov, Dimitar Alexandrov, James Glass, and Preslav Nakov. 2018. Predicting factuality of reporting and bias of news media sources. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 3528–3539, Association for Computational Linguis… find
  19. Bamman, David, Jacob Eisenstein, and Tyler Schnoebelen. 2014. Gender identity and lexical variation in social media. Journal of Sociolinguistics, 18(2):135–160. find
  20. Bamman, David, Brendan O’Connor, and Noah A. Smith. 2013. Learning latent personas of film characters. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 352–361, Association for Computational Linguistics, Sofia, Bulgaria. find
  21. Bamman, David and Noah A. Smith. 2015. Open extraction of fine-grained political statements. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 76–85, Association for Computational Linguistics, Lisbon, Portugal. find
  22. Bang, Yejin, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al. 2023. A multitask, multilingual, multimodal evaluation of chatgpt on reasoning, hallucination, and interactivity. ArXiv preprint, abs/2302.04023. find our card
  23. Barberá, Pablo, Ning Wang, Richard Bonneau, John T Jost, Jonathan Nagler, Joshua Tucker, and Sandra González-Bailón. 2015. The critical periphery in the growth of social protests. PloS one, 10(11):e0143611. find
  24. Beltagy, Iz, Matthew E Peters, and Arman Cohan. 2020. Longformer: The long-document transformer. ArXiv preprint, abs/2004.05150. find
  25. Belz, Anja and Eric Kow. 2010. Comparing rating scales and preference judgements in language evaluation. In Proceedings of the 6th International Natural Language Generation Conference. find
  26. Bender, Emily M, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Computational Linguistics conference on fairness, accountability, and transparency, pages 610–623. find
  27. Berelson, Bernard. 1952. Content analysis in communication research. van den Berg, Esther, Katharina Korfhage, Josef Ruppenhofer, Michael Wiegand, and Katja Markert. 2020. Doctor who? framing through names and titles in German. In Proceedings of the 12th Language Resources and Evaluation Conference,… find
  28. Bhatia, Sudeep. 2017. Associative judgment and vector space semantics. Psychological review, 124(1):1. find
  29. Bicchieri, Cristina. 2005. The grammar of society: The nature and dynamics of social norms. Cambridge University Press. find
  30. Black, Ryan C, Sarah A Treul, Timothy R Johnson, and Jerry Goldman. 2011. Emotions, oral arguments, and supreme court decision making. The Journal of Politics, 73(2):572–581. find
  31. Blodgett, Su Lin, Solon Barocas, Hal Daumé III, and Hanna Wallach. 2020. Language (technology) is power: A critical survey of “bias” in NLP. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 5454–5476, Association for Computational Linguistics, Online. find our card
  32. Bollen, Johan, Huina Mao, and Xiaojun Zeng. 2011. Twitter mood predicts the stock market. Journal of computational science, 2(1):1–8. find
  33. Bommasani, Rishi, Kathleen A Creel, Ananya Kumar, Dan Jurafsky, and Percy S Liang. 2022. Picking on the same person: Does algorithmic monoculture lead to outcome homogenization? Advances in Neural Information Processing Systems, 35:3663–3678. find
  34. Bommasani, Rishi, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al. 2021. On the opportunities and risks of foundation models. ArXiv preprint, abs/2108.07258. find our card
  35. Borchers, Conrad, Dalia Gala, Benjamin Gilburt, Eduard Oravkin, Wilfried Bounsi, Yuki M Asano, and Hannah Kirk. 2022. Looking for a handsome carpenter! debiasing GPT-3 job advertisements. In Proceedings of the 4th Workshop on Gender Bias in Natural Language Processing (GeBNLP), pages 212–224, Associ… find
  36. Box-Steffensmeier, Janet M and Bradford S Jones. 2004. Event history modeling: A guide for social scientists. Cambridge University Press. find
  37. Boyd, Ryan L, Kate G Blackburn, and James W Pennebaker. 2020. The narrative arc: Revealing core narrative structures through text analysis. Science advances, 6(32):eaba2196. find
  38. Brahman, Faeze and Snigdha Chaturvedi. 2020. Modeling protagonist emotions for emotion-aware storytelling. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5277–5294, Association for Computational Linguistics, Online. find
  39. Bramsen, Philip, Martha Escobar-Molano, Ami Patel, and Rafael Alonso. 2011. Extracting social power relationships from natural language. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 773–782, Association for Computation… find
  40. Brooke, Julian, Adam Hammond, and Timothy Baldwin. 2016. Bootstrapped text-level named entity recognition for literature. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 344–350, Association for Computational Linguistics, Ber… find
  41. Brown, Penelope and Stephen C Levinson. 1987. Politeness: Some universals in language usage, volume 4. Cambridge university press. find
  42. Brown, Tom B., Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter,… find
  43. Bucholtz, Mary and Kira Hall. 2005. Identity and interaction: A sociocultural linguistic approach. Discourse studies, 7(4-5):585–614. find
  44. Ziems, Held, Shaikh, Chen, Zhang, Yang Buechel, Sven, Anneke Buffone, Barry Slaff, Lyle Ungar, and João Sedoc. 2018. Modeling empathy and distress in reaction to news stories. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 4758–4765, Association for… find
  45. Bunt, Harry, Jan Alexandersson, Jean Carletta, Jae-Woong Choe, Alex Chengyu Fang, Koiti Hasida, Kiyong Lee, Volha Petukhova, Andrei Popescu-Belis, Laurent Romary, Claudia Soria, and David Traum. 2010. Towards an ISO standard for dialogue act annotation. In Proceedings of the Seventh International Co… find our card
  46. Burke, Moira and Robert Kraut. 2008. Mind your ps and qs: the impact of politeness and rudeness in online communities. In Proceedings of the 2008 ACM conference on Computer supported cooperative work, pages 281–284. find
  47. Caciularu, Avi, Arman Cohan, Iz Beltagy, Matthew E Peters, Arie Cattan, and Ido Dagan. 2021. Cdlm: Cross-document language modeling. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 2648–2662. find
  48. Carlini, Nicholas, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al. 2021. Extracting training data from large language models. In 30th USENIX Security Symposium (USENIX Security 21), pages 2633–2650. find our card
  49. Carlo, Valerio Di, Federico Bianchi, and Matteo Palmonari. 2019. Training temporal word embeddings with a compass. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symp… find
  50. Centola, Damon, Joshua Becker, Devon Brackbill, and Andrea Baronchelli. 2018. Experimental evidence for tipping points in social convention. Science, 360(6393):1116–1119. find
  51. Chaganty, Arun, Stephen Mussmann, and Percy Liang. 2018. The price of debiasing automatic metrics in natural language Can LLMs Transform CSS? evalaution. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 643–653, Association for… find
  52. Chakrabarty, Tuhin, Debanjan Ghosh, Adam Poliak, and Smaranda Muresan. 2021. Figurative language in recognizing textual entailment. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 3354–3361, Association for Computational Linguistics, Online. find
  53. Chakrabarty, Tuhin, Arkadiy Saakyan, Debanjan Ghosh, and Smaranda Muresan. 2022. Flute: Figurative language understanding through textual explanations. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 7139–7159. find
  54. Chambers, Nathanael and Dan Jurafsky. 2008. Unsupervised learning of narrative event chains. In Proceedings of ACL-08: HLT, pages 789–797, Association for Computational Linguistics, Columbus, Ohio. find
  55. Chang, Jonathan, Jordan L. Boyd-Graber, Sean Gerrish, Chong Wang, and David M. Blei. 2009. Reading tea leaves: How humans interpret topic models. In Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting he… find our card
  56. Chang, Jonathan P., Caleb Chiam, Liye Fu, Andrew Wang, Justine Zhang, and Cristian Danescu-Niculescu-Mizil. 2020. ConvoKit: A toolkit for the analysis of conversations. In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 57–60, Association for Com… find
  57. Chen, Derek, Zhou Yu, and Samuel Bowman. 2022. Clean or annotate: How to spend a limited data collection budget. In Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing, pages 152–168. find
  58. Chen, Peng-Yu and Von-Wun Soo. 2018. Humor recognition using deep learning. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 113–117, Association for Computational Linguis… find
  59. Computational Linguistics Cheng, Justin, Lada A. Adamic, Jon M. Kleinberg, and Jure Leskovec. 2016. Do cascades recur? In Proceedings of the 25th International Conference on World Wide Web, WWW 2016, Montreal, Canada, April 11 - 15, 2016, pages 671–681, ACM. find
  60. Cheng, Justin, Michael Bernstein, Cristian Danescu-Niculescu-Mizil, and Jure Leskovec. 2017. Anyone can become a troll: Causes of trolling behavior in online discussions. In Proceedings of the 2017 ACM conference on computer supported cooperative work and social computing, pages 1217–1230. find
  61. Cheng, Justin, Cristian Danescu-Niculescu-Mizil, and Jure Leskovec. 2015. Antisocial behavior in online discussion communities. In Proceedings of the international aaai conference on web and social media, volume 9, pages 61–70. find
  62. Child, Rewon, Scott Gray, Alec Radford, and Ilya Sutskever. 2019. Generating long sequences with sparse transformers. ArXiv preprint, abs/1904.10509. find
  63. Christiano, Paul F., Jan Leike, Tom B. Brown, Miljan Martic, Shane Legg, and Dario Amodei. 2017. Deep reinforcement learning from human preferences. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beac… find
  64. Chu, Eric, Jacob Andreas, Stephen Ansolabehere, and Deb Roy. 2023. Language models trained on media diets can predict public opinion. ArXiv preprint, abs/2303.16779. — [arXiv:2303.16779](https://arxiv.org/abs/2303.16779) find
  65. Chu, Eric, Prashanth Vijayaraghavan, and Deb Roy. 2018. Learning personas from dialogue with attentive memory networks. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2638–2646, Association for Computational Linguistics, Brussels, Belgium. find
  66. Chung, Hyung Won, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2022. Scaling instruction-finetuned language models. ArXiv preprint, abs/2210.11416. find
  67. Cialdini, Robert B. 2003. Influence. Influence At Work. find
  68. Coll Ardanuy, Mariona, Federico Nanni, Kaspar Beelen, Kasra Hosseini, Ruth Ahnert, Jon Lawrence, Katherine McDonough, Giorgia Tolfo, Daniel CS Wilson, and Barbara McGillivray. 2020. find
  69. Volume 50, Number 1 Living machines: A study of atypical animacy. In Proceedings of the 28th International Conference on Computational Linguistics, pages 4534–4545, International Committee on Computational Linguistics, Barcelona, Spain (Online). Cotfas, Liviu-Adrian, Camelia Delcea, Ioan Roxin, Cori… find
  70. Coulton, Paul, Jonny Huck, Andrew Hudson-Smith, Ralph Barthel, Panagiotis Mavros, Jennifer Roberts, and Philip Powell. 2014. Designing interactive systems to encourage empathy between users. In Proceedings of the 2014 companion publication on Designing interactive systems. pages 13–16. find
  71. Craig, Holly K and Julie A Washington. 2002. Oral language expectations for african american preschoolers and kindergartners. find
  72. Danescu-Niculescu-Mizil, Cristian, Lillian Lee, Bo Pang, and Jon M. Kleinberg. 2012. Echoes of power: language effects and power differences in social interaction. In Proceedings of the 21st World Wide Web Conference 2012, WWW 2012, Lyon, France, April 16-20, 2012, pages 699–708, ACM. find
  73. Danescu-Niculescu-Mizil, Cristian, Moritz Sudhof, Dan Jurafsky, Jure Leskovec, and Christopher Potts. 2013. A computational approach to politeness with application to social factors. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), p… find our card
  74. Dang, Hoa Trang. 2005. Overview of duc 2005. In Proceedings of the document understanding conference, volume 2005, pages 1–12, Citeseer. find
  75. Davies, Catherine E. 2017. Sociolinguistic approaches to humor. In The Routledge handbook of language and humor. Routledge, pages 472–488. find
  76. Del Tredici, Marco and Raquel Fernández. 2017. Semantic variation in online communities of practice. In IWCS 2017 - 12th International Conference on Computational Semantics - Long papers. find
  77. DeLozier, Grant, Ben Wing, Jason Baldridge, and Scott Nesbit. 2016. Creating a novel geolocation corpus from historical texts. In Proceedings of the 10th Linguistic Annotation Ziems, Held, Shaikh, Chen, Zhang, Yang Workshop held in conjunction with ACL 2016 (LAW-X 2016), pages 188–198, Association f… find
  78. Demszky, Dorottya, Nikhil Garg, Rob Voigt, James Zou, Jesse Shapiro, Matthew Gentzkow, and Dan Jurafsky. 2019. Analyzing polarization in social media: Method and application to tweets on 21 mass shootings. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Com… find
  79. Demszky, Dorottya, Devyani Sharma, Jonathan Clark, Vinodkumar Prabhakaran, and Jacob Eisenstein. 2021. Learning to recognize dialect features. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 2315… find
  80. Dhamala, Jwala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, and Rahul Gupta. 2021. Bold: Dataset and metrics for measuring biases in open-ended language generation. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pages 862–87… find
  81. DiMaggio, Paul. 2015. Adapting computational text analysis to social science (and vice versa). Big Data & Society, 2(2):2053951715602908. find
  82. DiMaggio, Paul, Manish Nag, and David Blei. 2013. Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of us government arts funding. Poetics, 41(6):570–606. find
  83. Dobson, James E. 2019. Critical digital humanities: the search for a methodology. University of Illinois Press. find
  84. Easley, David and Jon Kleinberg. 2010. Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge university press. find
  85. Egami, Naoki, Musashi Jacobs-Harukawa, Brandon M Stewart, and Hanying Wei. 2023. Using large language model annotations for valid downstream statistical inference in social science: Design-based semi-supervised learning. ArXiv preprint, abs/2306.04746. — [arXiv:2306.04746](https://arxiv.org/abs/2306.04746) find
  86. Eisenstein, Jacob. 2012. Mapping the geographical diffusion of new words. find
  87. Can LLMs Transform CSS? ArXiv preprint, abs/1210.5268. — [arXiv:1210.5268](https://arxiv.org/abs/1210.5268) find
  88. Eisenstein, Jacob, Brendan O’Connor, Noah A Smith, and Eric P Xing. 2014. Diffusion of lexical change in social media. PloS one, 9(11):e113114. find
  89. Eisenstein, Jacob, Vinodkumar Prabhakaran, Clara Rivera, Dorottya Demszky, and Devyani Sharma. 2023. Md3: The multi-dialect dataset of dialogues. ArXiv preprint, abs/2305.11355. — [arXiv:2305.11355](https://arxiv.org/abs/2305.11355) find
  90. Eisenstein, Jacob, Noah A. Smith, and Eric P. Xing. 2011. Discovering sociolinguistic associations with structured sparsity. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 1365–1374, Association for Computational Linguis… find
  91. Ellsberg, Daniel. 1961. Risk, ambiguity, and the savage axioms. The quarterly journal of economics, 75(4):643–669. find
  92. ElSherief, Mai, Caleb Ziems, David Muchlinski, Vaishnavi Anupindi, Jordyn Seybolt, Munmun De Choudhury, and Diyi Yang. 2021. Latent hatred: A benchmark for understanding implicit hate speech. ArXiv preprint, abs/2109.05322. find our card
  93. Entman, Robert M. 1993. Framing: Toward clarification of a fractured paradigm. Journal of communication, 43(4):51–58. find
  94. Evans, James A and Pedro Aceves. 2016. Machine translation: Mining text for social theory. Annual review of sociology, 42:21–50. find
  95. Fabbri, Alexander R, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021. Summeval: Re-evaluating summarization evaluation. Transactions of the Association for Computational Linguistics, 9:391–409. find
  96. Fazeen, Mohamed, Ram Dantu, and Parthasarathy Guturu. 2011. Identification of leaders, lurkers, associates and spammers in a social network: context-dependent and context-independent approaches. Social Network Analysis and Mining, 1(3):241–254. find
  97. Field, Anjalie, Doron Kliger, Shuly Wintner, Jennifer Pan, Dan Jurafsky, and Yulia Tsvetkov. 2018. Framing and agenda-setting in Russian news: a computational analysis of intricate political strategies. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages… find
  98. Flores, René D. 2017. Do anti-immigrant laws shape public sentiment? a study of Computational Linguistics arizona’s sb 1070 using twitter data. American Journal of Sociology, 123(2):333–384. find
  99. Gabriel, Saadia, Skyler Hallinan, Maarten Sap, Pemi Nguyen, Franziska Roesner, Eunsol Choi, and Yejin Choi. 2022. Misinfo reaction frames: Reasoning about readers’ reactions to news headlines. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long… find
  100. Gao, Ge, Eunsol Choi, Yejin Choi, and Luke Zettlemoyer. 2018. Neural metaphor detection in context. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 607–613, Association for Computational Linguistics, Brussels, Belgium. find
  101. Garfinkel, Harold. 2016. Studies in ethnomethodology. In Social Theory Re-Wired. Routledge, pages 85–95. find
  102. Garg, Nikhil, Londa Schiebinger, Dan Jurafsky, and James Zou. 2018. Word embeddings quantify 100 years of gender and ethnic stereotypes. Proceedings of the National Academy of Sciences, 115(16):E3635–E3644. find
  103. Gerber, Alan S, Gregory A Huber, David Doherty, Conor M Dowling, and Shang E Ha. 2010. Personality and political attitudes: Relationships across issue domains and political contexts. American Political Science Review, 104(1):111–133. find
  104. Gilardi, Fabrizio, Meysam Alizadeh, and Maël Kubli. 2023. Chatgpt outperforms crowd-workers for text-annotation tasks. ArXiv preprint, abs/2303.15056. find our card
  105. Golder, Scott A and Michael W Macy. 2014. Digital footprints: Opportunities and challenges for online social research. Annual Review of Sociology, 40:129–152. find
  106. Gomez-Zara, Diego, Miriam Boon, and Larry Birnbaum. 2018. Who is the hero, the villain, and the victim? detection of roles in news articles using natural language techniques. In 23rd International Conference on Intelligent User Interfaces, pages 311–315. find
  107. Goyal, Tanya, Junyi Jessy Li, and Greg Durrett. 2022. News summarization and evaluation in the era of gpt-3. ArXiv preprint, abs/2209.12356. find
  108. Graham, Elizabeth E. 1995. The involvement of sense of humor in the development of social relationships. Communication Reports, 8(2):158–169. find
  109. Grimmer, Justin. 2010. A bayesian hierarchical topic model for political texts: Measuring expressed agendas in senate press releases. Political Analysis, 18(1):1–35. find
  110. Gross, Justin H, Brice Acree, Yanchuan Sim, and Noah A Smith. 2013. Testing the etch-a-sketch hypothesis: a computational analysis of mitt romney’s ideological makeover during the 2012 primary vs. general elections. In APSA 2013 Annual Meeting Paper, American Political Science Association 2013 Annua… find
  111. Grudin, Jonathan. 2006. Why personas work: The psychological evidence. The persona lifecycle, 12:642–664. find
  112. Hamilton, William L., Jure Leskovec, and Dan Jurafsky. 2016a. Cultural shift or linguistic drift? comparing two computational measures of semantic change. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 2116–2121, Association for Computational Linguis… find
  113. Hamilton, William L., Jure Leskovec, and Dan Jurafsky. 2016b. Diachronic word embeddings reveal statistical laws of semantic change. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1489–1501, Association for Computational Ling… find our card
  114. Harzing, Anne-Wil, Joyce Baldueza, Wilhelm Barner-Rasmussen, Cordula Barzantny, Anne Canabal, Anabella Davila, Alvaro Espejo, Rita Ferreira, Axele Giroud, Kathrin Koester, et al. 2009. Rating versus ranking: What is the best way to reduce response and language bias in cross-national research? Intern… find
  115. Hashim, Safair Safwat Mohammed and Suhair Safwat. 2015. Speech acts in political speeches. Journal of Modern Education Review, 5(7):699–706. find
  116. Hendrycks, Dan, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021. Measuring massive multitask language understanding. In International Conference on Learning Representations. find our card
  117. Herring, Susan C. 1994. Politeness in computer culture: Why women thank and men flame. In Cultural performances: Proceedings of the third Berkeley women and language conference, pages 278–294. find
  118. Hirsh, Jacob B, Sonia K Kang, and Galen V Bodenhausen. 2012. Personalized persuasion: Tailoring persuasive appeals to recipients’ personality traits. Psychological science, 23(6):578–581. find
  119. Ziems, Held, Shaikh, Chen, Zhang, Yang Hoffmann, Jordan, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, et al. 2022. Training compute-optimal large language models. ArXiv preprint, abs/2203.155… find
  120. Hofman, Jake M, Amit Sharma, and Duncan J Watts. 2017. Prediction and explanation in social systems. Science, 355(6324):486–488. find
  121. Huguet Cabot, Pere-Lluís, Verna Dankers, David Abadi, Agneta Fischer, and Ekaterina Shutova. 2020. The Pragmatics behind Politics: Modelling Metaphor, Framing and Emotion in Political Discourse. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4479–4488, Association fo… find
  122. Hürriyetoğlu, Ali, Hristo Tanev, Vanni Zavarella, Jakub Piskorski, Reyyan Yeniterzi, Deniz Yuret, and Aline Villavicencio. 2021. Challenges and applications of automated extraction of socio-political events from text (CASE 2021): Workshop and shared task report. In Proceedings of the 4th Workshop o… find
  123. Hutchby, Ian and Robin Wooffitt. 2008. Conversation analysis. Polity. find
  124. Ignatow, Gabe and Rada Mihalcea. 2016. Text mining: A guidebook for the social sciences. Sage Publications. find
  125. Iyengar, Shanto. 1990. Framing responsibility for political issues: The case of poverty. Political behavior, 12(1):19–40. find
  126. Iyer, Adith, Aditya Joshi, Sarvnaz Karimi, Ross Sparks, and Cecile Paris. 2019. Figurative usage detection of symptom words to improve personal health mention detection. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 1142–1147, Association for Compu… find
  127. Iyyer, Mohit, Peter Enns, Jordan Boyd-Graber, and Philip Resnik. 2014. Political ideology detection using recursive neural networks. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1113–1122, Association for Computational Ling… find
  128. Iyyer, Mohit, Anupam Guha, Snigdha Chaturvedi, Jordan Boyd-Graber, and Hal Daumé III. 2016. Feuding families and former Friends: Unsupervised learning for dynamic fictional relationships. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguis… find
  129. Jacobs, Arthur M and Annette Kinder. 2018. What makes a metaphor literary? answers from two computational studies. Metaphor and Symbol, 33(2):85–100. find
  130. Jahan, Labiba, Rahul Mittal, and Mark Finlayson. 2021. Inducing stereotypical character roles from plot structure. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 492–497. find
  131. Jelveh, Zubin, Bruce Kogut, and Suresh Naidu. 2014. Detecting latent ideology in expert text: Evidence from academic papers in economics. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1804–1809, Association for Computational Linguistics, Doh… find
  132. Jenhani, Ferdaous, Mohamed Salah Gouider, and Lamjed Ben Said. 2016. A hybrid approach for drug abuse events extraction from twitter. Procedia computer science, 96:1032–1040. find
  133. Jochim, Charles, Francesca Bonin, Roy Bar-Haim, and Noam Slonim. 2018. SLIDE - a sentiment lexicon of common idioms. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), European Language Resources Association (ELRA), Miyazaki, Japan. find
  134. Jockers, Matthew L and David Mimno. 2013. Significant themes in 19th-century literature. Poetics, 41(6):750–769. find
  135. Johnson, Kristen, I-Ta Lee, and Dan Goldwasser. 2017. Ideological phrase indicators for classification of political discourse framing on Twitter. In Proceedings of the Second Workshop on NLP and Computational Social Science, pages 90–99, Association for Computational Linguistics, Vancouver, Canada. find
  136. Jones, Erik and Jacob Steinhardt. 2022. Capturing failures of large language models via human cognitive biases. ArXiv preprint, abs/2202.12299. — [arXiv:2202.12299](https://arxiv.org/abs/2202.12299) find
  137. Joshi, Aditya, Pushpak Bhattacharyya, and Mark J Carman. 2017. Automatic sarcasm Computational Linguistics detection: A survey. ACM Computing Surveys (CSUR), 50(5):1–22. find
  138. Kaplan, Jared, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020. Scaling laws for neural language models. ArXiv preprint, abs/2001.08361. find
  139. Karpinska, Marzena, Nader Akoury, and Mohit Iyyer. 2021. The perils of using Mechanical Turk to evaluate open-ended text generation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 1265–1285, Association for Computational Linguistics, Online and Punta… find
  140. Kershaw, Daniel, Matthew Rowe, and Patrick Stacey. 2016. Towards modelling language innovation acceptance in online social networks. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, San Francisco, CA, USA, February 22-25, 2016, pages 553–562, ACM. find
  141. Kesarwani, Vaibhav, Diana Inkpen, Stan Szpakowicz, and Chris Tanasescu. 2017. Metaphor detection in a poetry corpus. In Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 1–9, Association for Computational Li… find
  142. Keuschnigg, Marc, Niclas Lovsjö, and Peter Hedström. 2018. Analytical sociology and computational social science. Journal of Computational Social Science, 1(1):3–14. find
  143. Kiela, Douwe, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, and Adina Williams. 2021. Dyn… find
  144. Kim, Tae-Yeol, Deog-Ro Lee, and Noel Yuen Shan Wong. 2016. Supervisor humor and employee outcomes: The role of social distance and affective trust in supervisor. Journal of Business and Psychology, 31:125–139. find
  145. Kim, Yoon, Yi-I Chiu, Kentaro Hanaki, Darshan Hegde, and Slav Petrov. 2014. find
  146. Volume 50, Number 1 Temporal analysis of language through neural language models. In Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science, pages 61–65, Association for Computational Linguistics, Baltimore, MD, USA. find
  147. King, Gary and Will Lowe. 2003. An automated information extraction tool for international conflict data with performance as good as human coders: A rare events evaluation design. International Organization, 57(3):617–642. find
  148. Kirby, Simon, Mike Dowman, and Thomas L Griffiths. 2007. Innateness and culture in the evolution of language. Proceedings of the National Academy of Sciences, 104(12):5241–5245. find
  149. Kleinberg, Jon, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig, and Sendhil Mullainathan. 2018. Human decisions and machine predictions. The quarterly journal of economics, 133(1):237–293. find
  150. Kleinberg, Jon and Manish Raghavan. 2021. Algorithmic monoculture and social welfare. Proceedings of the National Academy of Sciences, 118(22):e2018340118. find
  151. Koralus, Philipp and Vincent Wang-Maścianica. 2023. Humans in humans out: On gpt converging toward common sense in both success and failure. ArXiv preprint, abs/2303.17276. find
  152. Kosinski, Michal, David Stillwell, and Thore Graepel. 2013. Private traits and attributes are predictable from digital records of human behavior. Proceedings of the national academy of sciences, 110(15):5802–5805. find
  153. Kozlowski, Austin C, Matt Taddy, and James A Evans. 2019. The geometry of culture: Analyzing the meanings of class through word embeddings. American Sociological Review, 84(5):905–949. find
  154. Kuhn, Thomas S. 1962. The structure of Scientific Revolutions. The University of Chicago Press. find
  155. Kuipers, Giselinde. 2009. Humor styles and symbolic boundaries. find
  156. Kulkarni, Vivek, Rami Al-Rfou, Bryan Perozzi, and Steven Skiena. 2015. Statistically significant detection of linguistic change. In Proceedings of the 24th International Conference on World Wide Web, WWW 2015, Florence, Italy, May 18-22, 2015, pages 625–635, ACM. find
  157. Kwak, Haewoon, Jeremy Blackburn, and Seungyeop Han. 2015. Exploring cyberbullying and other toxic behavior in team competition online games. In Proceedings of the 33rd Annual ACM Ziems, Held, Shaikh, Chen, Zhang, Yang Conference on Human Factors in Computing Systems, CHI 2015, Seoul, Republic of Kor… find
  158. Labatut, Vincent and Xavier Bost. 2019. Extraction and analysis of fictional character networks: A survey. ACM Computing Surveys (CSUR), 52(5):1–40. find
  159. Lai, Mirko, Alessandra Teresa Cignarella, Delia Irazú Hernández Farías, Cristina Bosco, Viviana Patti, and Paolo Rosso. 2020. Multilingual stance detection in social media political debates. Computer Speech & Language, 63:101075. find
  160. Lai, Viet, Minh Van Nguyen, Heidi Kaufman, and Thien Huu Nguyen. 2021. Event extraction from historical texts: A new dataset for black rebellions. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 2390–2400, Association for Computational Linguistics, Online. find
  161. Lazer, David, Alex Pentland, Lada Adamic, Sinan Aral, Albert-László Barabási, Devon Brewer, Nicholas Christakis, Noshir Contractor, James Fowler, Myron Gutmann, et al. 2009. Computational social science. Science, 323(5915):721–723. find
  162. Lazer, David MJ, Matthew A Baum, Yochai Benkler, Adam J Berinsky, Kelly M Greenhill, Filippo Menczer, Miriam J Metzger, Brendan Nyhan, Gordon Pennycook, David Rothschild, et al. 2018. The science of fake news. Science, 359(6380):1094–1096. find
  163. Lazer, David MJ, Alex Pentland, Duncan J Watts, Sinan Aral, Susan Athey, Noshir Contractor, Deen Freelon, Sandra Gonzalez-Bailon, Gary King, Helen Margetts, et al. 2020. Computational social science: Obstacles and opportunities. Science, 369(6507):1060–1062. find
  164. Lemmens, Jens, Ilia Markov, and Walter Daelemans. 2021. Improving hate speech type and target detection with hateful metaphor features. In Proceedings of the Fourth Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda, pages 7–16, Association for Computational Linguistics… find
  165. Leskovec, Jure, Lars Backstrom, and Jon Kleinberg. 2009. Meme-tracking and the dynamics of the news cycle. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 497–506. find
  166. Li, Sha, Heng Ji, and Jiawei Han. 2021. Document-level event argument extraction by conditional generation. In Proceedings of the 2021 Conference of the Can LLMs Transform CSS? find our card
  167. North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 894–908, Association for Computational Linguistics, Online. find
  168. Li, Shuang, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, et al. 2022. Pre-trained language models for interactive decision-making. Advances in Neural Information Processing Systems, 35:31199–31212. find
  169. Liang, Percy, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, et al. 2022. Holistic evaluation of language models. ArXiv preprint, abs/2211.09110. find
  170. Liu, Chia-Wei, Ryan Lowe, Iulian Serban, Mike Noseworthy, Laurent Charlin, and Joelle Pineau. 2016. How NOT to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation. In Proceedings of the 2016 Conference on Empirical Methods in Natural… find
  171. Liu, Yinhan, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. Roberta: A robustly optimized bert pretraining approach. find
  172. Lucy, Li and David Bamman. 2021. Gender and representation bias in GPT-3 generated stories. In Proceedings of the Third Workshop on Narrative Understanding, pages 48–55, Association for Computational Linguistics, Virtual. find
  173. Luo, Yiwei, Dallas Card, and Dan Jurafsky. 2020a. Desmog: Detecting stance in media on global warming. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, pages 3296–3315. find
  174. Luo, Yiwei, Dallas Card, and Dan Jurafsky. 2020b. Detecting stance in media on global warming. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 3296–3315, Association for Computational Linguistics, Online. find
  175. Ma, Yukun, Khanh Linh Nguyen, Frank Z Xing, and Erik Cambria. 2020. A survey on empathetic dialogue systems. Information Fusion, 64:50–70. find
  176. Machina, Mark J. 1987. Choice under uncertainty: Problems solved and Computational Linguistics unsolved. Journal of Economic perspectives, 1(1):121–154. find
  177. Maki, Keith, Michael Yoder, Yohan Jo, and Carolyn Rosé. 2017. Roles and success in Wikipedia talk pages: Identifying latent patterns of behavior. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1026–1035, Asian Federation of N… find
  178. Markiewicz, Dorothy. 1974. Effects of humor on persuasion. Sociometry, pages 407–422. find
  179. Martin, Rod A and Thomas Ford. 2018. The psychology of humor: An integrative approach. Academic press. find
  180. Martino, Giovanni Da San, Stefano Cresci, Alberto Barrón-Cedeño, Seunghak Yu, Roberto Di Pietro, and Preslav Nakov. 2020. A survey on computational propaganda detection. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020, pages 4826–4832, ijcai.o… find
  181. Mathew, Binny, Anurag Illendula, Punyajoy Saha, Soumya Sarkar, Pawan Goyal, and Animesh Mukherjee. 2020. Hate begets hate: A temporal study of hate speech. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW2):1–24. find
  182. Mendelsohn, Julia, Ceren Budak, and David Jurgens. 2021. Modeling framing in immigration discourse on social media. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 2219–2263, Association for Comp… find
  183. Mihalcea, Rada and Vivi Nastase. 2012. Word epoch disambiguation: Finding how words change over time. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 259–263, Association for Computational Linguistics, Jeju Island, Korea. find
  184. Mihalcea, Rada and Carlo Strapparava. 2005. Making computers laugh: Investigations in automatic humor recognition. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, pages 531–538, Association for Computational Linguistics, Vanc… find
  185. Miller, Tim. 2019. Explanation in artificial intelligence: Insights from the social sciences. Artificial intelligence, 267:1–38. find our card
  186. Min, Bonan and Xiaoxi Zhao. 2019. Measure country-level socio-economic indicators with streaming news: An empirical study. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP… find
  187. Mishra, Abhijit, Tarun Tater, and Karthik Sankaranarayanan. 2019. A modular architecture for unsupervised sarcasm generation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJC… find
  188. Mohammad, Saif, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016. SemEval-2016 task 6: Detecting stance in tweets. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pages 31–41, Association for Computational Linguistics, San Diego, Cal… find
  189. Murphy, Kevin M and Andrei Shleifer. 2004. Persuasion in politics. American Economic Review, 94(2):435–439. find
  190. Murray, Michael et al. 2015. Narrative psychology. Qualitative psychology: A practical guide to research methods, pages 85–107. find
  191. Muthukrishna, Michael, Adrian V Bell, Joseph Henrich, Cameron M Curtin, Alexander Gedranovich, Jason McInerney, and Braden Thue. 2020. Beyond western, educated, industrial, rich, and democratic (weird) psychology: Measuring and mapping scales of cultural and psychological distance. Psychological sci… find
  192. Nelson, Laura K. 2015. Political logics as cultural memory: cognitive structures, local continuities, and women’s organizations in chicago and new york city. Work. Pap. Kellogg School Manag., Northwestern Univ. find
  193. Nelson, Laura K. 2021. Cycles of conflict, a century of continuity: the impact of persistent place-based political logics on social movement strategy. American Journal of Sociology, 127(1):1–59. find
  194. Nguyen, Dong, A Seza Doğruöz, Carolyn P Rosé, and Franciska de Jong. 2016. Computational sociolinguistics: A survey. Computational linguistics, 42(3):537–593. find
  195. Ziems, Held, Shaikh, Chen, Zhang, Yang Nguyen, Thien Hai and Kiyoaki Shirai. 2015. Topic modeling based sentiment analysis on social media for stock market prediction. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conferenc… find
  196. Nguyen, Thong, Andrew Yates, Ayah Zirikly, Bart Desmet, and Arman Cohan. 2022. Improving the generalizability of depression detection by leveraging clinical questionnaires. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 8446–… find
  197. Niculae, Vlad and Cristian Danescu-Niculescu-Mizil. 2014. Brighter than gold: Figurative language in user generated comparisons. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 2008–2018, Association for Computational Linguistics, Doha, Qatar. find
  198. Novikova, Jekaterina, Ondřej Dušek, Amanda Cercas Curry, and Verena Rieser. 2017. Why we need new evaluation metrics for NLG. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2241–2252, Association for Computational Linguistics, Copenhagen, Denmark. find
  199. Ofer, Dan and Dafna Shahaf. 2022. Cards against AI: Predicting humor in a fill-in-the-blank party game. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 5397–5403, Association for Computational Linguistics, Abu Dhabi, United Arab Emirates. find
  200. Omitaomu, Damilola, Shabnam Tafreshi, Tingting Liu, Sven Buechel, Chris Callison-Burch, Johannes Eichstaedt, Lyle Ungar, and João Sedoc. 2022. Empathic conversations: A multi-level dataset of contextualized conversations. ArXiv preprint, abs/2205.12698. — [arXiv:2205.12698](https://arxiv.org/abs/2205.12698) find
  201. OpenAI. 2023. Gpt-4 technical report. find our card
  202. Ortu, Marco, Alessandro Murgia, Giuseppe Destefanis, Parastou Tourani, Roberto Tonelli, Michele Marchesi, and Bram Adams. 2016. The emotional side of software developers in jira. In Proceedings of the 13th international conference on mining software repositories, pages 480–483. find
  203. Ouyang, Long, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Can LLMs Transform CSS? find
  204. Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022. Training language models to follow instructions with human feedback. Advances in Neural Information Processing Systems, 35:27730–27744. find
  205. Paltridge, Brian and Jill Burton. 2000. Making sense of discourse analysis. Antipodean Educational Enterprises Gold Coast, Queensland. find
  206. Park, Joon Sung, Joseph C. O’Brien, Carrie J. Cai, Meredith Ringel Morris, Percy Liang, and Michael S. Bernstein. 2023. Generative agents: Interactive simulacra of human behavior. find
  207. Park, Joon Sung, Lindsay Popowski, Carrie Cai, Meredith Ringel Morris, Percy Liang, and Michael S Bernstein. 2022. Social simulacra: Creating populated prototypes for social computing systems. In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, pages 1–18. find
  208. Pennebaker, James W and Laura A King. 1999. Linguistic styles: language use as an individual difference. Journal of personality and social psychology, 77(6):1296. find
  209. Perez, Ethan, Douwe Kiela, and Kyunghyun Cho. 2021. True few-shot learning with language models. Advances in neural information processing systems, 34:11054–11070. find our card
  210. Pfeil, Ulrike and Panayiotis Zaphiris. 2007. Patterns of empathy in online communication. In Proceedings of the SIGCHI conference on Human factors in computing systems, pages 919–928. find
  211. Picard, Rosalind W. 2000. Affective computing. MIT press. find
  212. Pilehvar, Mohammad Taher and Jose Camacho-Collados. 2019. WiC: the word-in-context dataset for evaluating context-sensitive meaning representations. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volu… find our card
  213. Piper, Andrew, Richard Jean So, and David Bamman. 2021. Narrative theory for computational narrative understanding. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 298–311. find
  214. Plutchik, Robert. 1980. A general psychoevolutionary theory of emotion. In Theories of emotion. Elsevier, pages 3–33. find
  215. Computational Linguistics Post, Matt. 2018. A call for clarity in reporting BLEU scores. In Proceedings of the Third Conference on Machine Translation: Research Papers, pages 186–191, Association for Computational Linguistics, Brussels, Belgium. find our card
  216. Prabhakaran, Vinodkumar, Owen Rambow, and Mona Diab. 2012. Predicting overt display of power in written dialogs. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 518–522, Association for Computati… find
  217. Prabhakaran, Vinodkumar, Emily E. Reid, and Owen Rambow. 2014. Gender and power: How gender and gender environment affect manifestations of power. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1965–1976, Association for Computational Linguis… find
  218. Preece, Jenny. 1998. Empathic communities: Reaching out across the web. interactions, 5(2):32–43. find
  219. Preoţiuc-Pietro, Daniel, Vasileios Lampos, and Nikolaos Aletras. 2015. An analysis of the user occupational class through Twitter content. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Proces… find
  220. Preoţiuc-Pietro, Daniel, Ye Liu, Daniel Hopkins, and Lyle Ungar. 2017. Beyond binary labels: Political ideology prediction of Twitter users. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 729–740, Association for Computation… find
  221. Purschke, Christoph and Dirk Hovy. 2019. Lörres, möppes, and the swiss.(re) discovering regional patterns in anonymous social media data. Journal of Linguistic Geography, 7(2):113–134. find
  222. Qin, Chengwei, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, and Diyi Yang. 2023. Is chatgpt a general-purpose natural language processing task solver? ArXiv preprint, abs/2302.06476. find our card
  223. Raffel, Colin, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Volume 50, Number 1 find
  224. Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020. Exploring the limits of transfer learning with a unified text-to-text transformer. The Journal of Machine Learning Research, 21(1):5485–5551. find
  225. Raji, Deborah, Emily Denton, Emily M. Bender, Alex Hanna, and Amandalynne Paullada. 2021. Ai and the everything in the whole wide world benchmark. In Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, volume 1, Curran. find
  226. Ratner, Alexander, Stephen H Bach, Henry Ehrenberg, Jason Fries, Sen Wu, and Christopher Ré. 2017. Snorkel: Rapid training data creation with weak supervision. In Proceedings of the VLDB Endowment. International Conference on Very Large Data Bases, volume 11, page 269, NIH Public Access. find
  227. Ribeiro, Marco Tulio and Scott Lundberg. 2022. Adaptive testing and debugging of nlp models. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 3253–3267. find
  228. Rogers, Anna, Olga Kovaleva, and Anna Rumshisky. 2019. Calls to action on social media: Potential for censorship and social impact. find
  229. EMNLP-IJCNLP 2019, page 36. find
  230. Rothbaum, Barbara Olasov, Elizabeth A Meadows, Patricia Resick, and David W Foy. 2000. Cognitive-behavioral therapy. find
  231. Roy, Shamik and Dan Goldwasser. 2020. Weakly supervised learning of nuanced frames for analyzing polarization in news media. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 7698–7716, Association for Computational Linguistics, Online. find
  232. Rudolph, Maja R. and David M. Blei. 2018. Dynamic embeddings for language evolution. In Proceedings of the 2018 World Wide Web Conference on World Wide Web, WWW 2018, Lyon, France, April 23-27, 2018, pages 1003–1011, ACM. find
  233. Ryskina, Maria, Ella Rabinovich, Taylor Berg-Kirkpatrick, David Mortensen, and Yulia Tsvetkov. 2020. Where new words are born: Distributional semantic analysis of neologisms and their semantic neighborhoods. In Proceedings of the Society for Computation in Linguistics 2020, pages 367–376, Associatio… find our card
  234. Sacks, Harvey. 1992. Lectures on conversation: Volume i. Malden, Massachusetts: Blackwell. find
  235. Ziems, Held, Shaikh, Chen, Zhang, Yang Saldias, Belen and Deb Roy. 2020. Exploring aspects of similarity between spoken personal narratives by disentangling them into narrative clause types. In Proceedings of the First Joint Workshop on Narrative Understanding, Storylines, and Events, pages 78–86, A… find
  236. Salganik, Matthew J, Peter Sheridan Dodds, and Duncan J Watts. 2006. Experimental study of inequality and unpredictability in an artificial cultural market. science, 311(5762):854–856. find
  237. Sanh, Victor, Albert Webson, Colin Raffel, Stephen Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, et al. Multitask prompted training enables zero-shot task generalization. In International Conference on Learning Representations. find our card
  238. Santhanam, Sashank and Samira Shaikh. 2019. Towards best experiment design for evaluating dialogue system output. In Proceedings of the 12th International Conference on Natural Language Generation, pages 88–94, Association for Computational Linguistics, Tokyo, Japan. find
  239. Santurkar, Shibani, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, and Tatsunori Hashimoto. 2023a. Whose opinions do language models reflect? find our card
  240. Santurkar, Shibani, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, and Tatsunori Hashimoto. 2023b. Whose opinions do language models reflect? ArXiv preprint, abs/2303.17548. find our card
  241. Sap, Maarten, Dallas Card, Saadia Gabriel, Yejin Choi, and Noah A. Smith. 2019. The risk of racial bias in hate speech detection. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 1668–1678, Association for Computational Linguistics, Florence, Italy. find our card
  242. Sap, Maarten, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A. Smith, and Yejin Choi. 2020a. Social bias frames: Reasoning about social and power implications of language. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 5477–5490, Association for C… find our card
  243. Sap, Maarten, Eric Horvitz, Yejin Choi, Noah A. Smith, and James Pennebaker. 2020b. Recollection versus imagination: Exploring human memory and cognition via neural language models. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages Can LLMs Transform C… find
  244. Sap, Maarten, Anna Jafarpour, Yejin Choi, Noah A Smith, James W Pennebaker, and Eric Horvitz. 2022. Quantifying the narrative flow of imagined versus autobiographical stories. Proceedings of the National Academy of Sciences, 119(45):e2211715119. find
  245. Sap, Maarten, Marcella Cindy Prasettio, Ari Holtzman, Hannah Rashkin, and Yejin Choi. 2017. Connotation frames of power and agency in modern films. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2329–2334, Association for Computational Linguistics, C… find
  246. Saravia, Elvis, Hsien-Chi Toby Liu, Yen-Hao Huang, Junlin Wu, and Yi-Shin Chen. 2018. CARER: Contextualized affect representations for emotion recognition. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 3687–3697, Association for Computational Lingui… find our card
  247. Schelling, Thomas C. 1971. Dynamic models of segregation. Journal of mathematical sociology, 1(2):143–186. find
  248. Schlechtweg, Dominik, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky, and Nina Tahmasebi. 2020. SemEval-2020 task 1: Unsupervised lexical semantic change detection. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1–23, International Committee for Computational Linguist… find our card
  249. Sech, Justin, Alexandra DeLucia, Anna L. Buczak, and Mark Dredze. 2020. Civil unrest on Twitter (CUT): A dataset of tweets to support research on civil unrest. In Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), pages 215–221, Association for Computational Linguistics, On… find
  250. Sellam, Thibault, Dipanjan Das, and Ankur Parikh. 2020. BLEURT: Learning robust metrics for text generation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7881–7892, Association for Computational Linguistics, Online. find
  251. Shah, Raj Sanjay, Faye Holt, Shirley Anugrah Hayati, Aastha Agarwal, Yi-Chia Wang, Robert E Kraut, and Diyi Yang. 2022. Modeling motivational interviewing strategies on an online peer-to-peer counseling platform. Proceedings of the Computational Linguistics ACM on Human-Computer Interaction, 6(CSCW2… find
  252. Shaikh, Omar, Jiaao Chen, Jon Saad-Falcon, Polo Chau, and Diyi Yang. 2020. Examining the ordering of rhetorical strategies in persuasive requests. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 1299–1306, Association for Computational Linguistics, Online. find
  253. Shaikh, Omar, Hongxin Zhang, William Held, Michael Bernstein, and Diyi Yang. 2022. On second thought, let’s not think step by step! bias and toxicity in zero-shot reasoning. ArXiv preprint, abs/2212.08061. find our card
  254. Sharma, Ashish, Inna W Lin, Adam S Miner, David C Atkins, and Tim Althoff. 2021. Towards facilitating empathic conversations in online mental health support: A reinforcement learning approach. In Proceedings of the Web Conference 2021, pages 194–205. find
  255. Sharma, Ashish, Adam Miner, David Atkins, and Tim Althoff. 2020. A computational approach to understanding empathy expressed in text-based mental health support. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5263–5276, Association for Comput… find our card
  256. Shen, Shirong, Guilin Qi, Zhen Li, Sheng Bi, and Lusheng Wang. 2020. Hierarchical Chinese legal event extraction via pedal attention mechanism. In Proceedings of the 28th International Conference on Computational Linguistics, pages 100–113, International Committee on Computational Linguistics, Barce… find
  257. Sheng, Emily, Kai-Wei Chang, Prem Natarajan, and Nanyun Peng. 2021. Societal biases in language generation: Progress and challenges. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (… find our card
  258. Sherman, Lawrence W. 1988. Humor and social distance in elementary school children. find
  259. Shmueli, Galit et al. 2010. To explain or to predict? Statistical science, 25(3):289–310. find
  260. Shubik, Martin. 1982. Game theory in the social sciences: concepts and solutions. find
  261. Siddiqua, Umme Aymun, Abu Nowshed Chy, and Masaki Aono. 2019. Tweet stance Volume 50, Number 1 detection using multi-kernel convolution and attentive lstm variants. IEICE TRANSACTIONS on Information and Systems, 102(12):2493–2503. find
  262. Silverman, David. 1998. Harvey Sacks: Social science and conversation analysis. Oxford University Press on Demand. find
  263. Sims, Matthew, Jong Ho Park, and David Bamman. 2019. Literary event detection. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3623–3634, Association for Computational Linguistics, Florence, Italy. find
  264. Snow, Rion, Brendan O’Connor, Daniel Jurafsky, and Andrew Ng. 2008. Cheap and fast – but is it good? evaluating non-expert annotations for natural language tasks. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 254–263, Association for Computational L… find
  265. Solaiman, Irene and Christy Dennison. 2021. Process for adapting language models to society (palms) with values-targeted datasets. Advances in Neural Information Processing Systems, 34:5861–5873. find
  266. Sprugnoli, Rachele and Sara Tonelli. 2019. Novel event detection and classification for historical texts. Computational Linguistics, 45(2):229–265. find
  267. Srivastava, Aarohi, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al. 2023. Beyond the imitation game: Quantifying and extrapolating the capabilities of language models. Transactions on Machine Learning… find our card
  268. Srivastava, Shashank, Snigdha Chaturvedi, and Tom M. Mitchell. 2016. Inferring interpersonal relations in narrative summaries. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA, pages 2807–2813, AAAI Press. find
  269. Stefanov, Peter, Kareem Darwish, Atanas Atanasov, and Preslav Nakov. 2020. Predicting the topical stance and political leaning of media using tweets. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 527–537, Association for Computational Linguistics,… find
  270. Stewart, Charles J, Craig Allen Smith, and Robert E Denton Jr. 2012. Persuasion and social movements. Waveland Press. find
  271. Ziems, Held, Shaikh, Chen, Zhang, Yang Stolcke, Andreas, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, Paul Taylor, Rachel Martin, Carol Van Ess-Dykema, and Marie Meteer. 2000. Dialogue act modeling for automatic tagging and recognition of conversational speech. Compu… find our card
  272. Stone, Philip J, Dexter C Dunphy, and Marshall S Smith. 1966. The general inquirer: A computer approach to content analysis. find
  273. Stowe, Kevin, Prasetya Utama, and Iryna Gurevych. 2022. IMPLI: Investigating NLI models’ performance on figurative language. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5375–5388, Association for Computational Linguistics,… find our card
  274. Suler, John. 2005. Contemporary media forum: The online disinhibition effect. International Journal of Applied Psychoanalytic Studies. find
  275. Tan, Chenhao, Lillian Lee, and Bo Pang. 2014. The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 175–185, Association for… find
  276. Tan, Chenhao, Vlad Niculae, Cristian Danescu-Niculescu-Mizil, and Lillian Lee. 2016. Winning arguments: Interaction dynamics and persuasion strategies in good-faith online discussions. In Proceedings of the 25th International Conference on World Wide Web, WWW 2016, Montreal, Canada, April 11 - 15, 2… find
  277. Taylor, Samuel Hardman, Dominic DiFranzo, Yoon Hyung Choi, Shruti Sannon, and Natalya N Bazarova. 2019. Accountability and empathy by design: Encouraging bystander intervention to cyberbullying on social media. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW):1–26. find
  278. Trope, Yaacov and Nira Liberman. 2010. Construal-level theory of psychological distance. Psychological review, 117(2):440. find
  279. Tufekci, Zeynep and Christopher Wilson. 2012. Social media and the decision to participate in political protest: Observations from tahrir square. Journal of communication, 62(2):363–379. find
  280. Vala, Hardik, David Jurgens, Andrew Piper, and Derek Ruths. 2015. Mr. bennet, his coachman, and the archbishop walk into a bar but only one of them gets recognized: On the difficulty of detecting characters in literary texts. In Proceedings of the 2015 Conference on Empirical Methods in Natural Lang… find
  281. Vosoughi, Soroush, Deb Roy, and Sinan Aral. 2018. The spread of true and false news online. science, 359(6380):1146–1151. find
  282. Wallach, Hanna M., Iain Murray, Ruslan Salakhutdinov, and David M. Mimno. 2009. Evaluation methods for topic models. In Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, Montreal, Quebec, Canada, June 14-18, 2009, volume 382 of ACM International Conference Proce… find
  283. Wang, Yizhong, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Atharva Naik, Arjun Ashok, Arut Selvan Dhanasekaran, Anjana Arunkumar, David Stap, et al. 2022. Super-naturalinstructions: Generalization via declarative instructions on 1600+ nlp tasks. In Proceedings of the 202… find
  284. Wardhaugh, Ronald and Janet M Fuller. 2021. An introduction to sociolinguistics. John Wiley & Sons. find
  285. Weller, Orion and Kevin Seppi. 2019. Humor detection: A transformer gets the last laugh. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 3621–3625, Association fo… find
  286. Welser, Howard T., Dan Cosley, Gueorgi Kossinets, Austin Lin, Fedor Dokshin, Geri Gay, and Marc Smith. 2011. Finding social roles in wikipedia. In Proceedings of the 2011 iConference, iConference ’11, pages 122–129, ACM, New York, NY, USA. find
  287. Wiegreffe, Sarah, Jack Hessel, Swabha Swayamdipta, Mark Riedl, and Yejin Choi. 2022. Reframing human-AI collaboration for generating free-text explanations. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologi… find
  288. Wu, Minghao and Alham Fikri Aji. 2023. Style over substance: Evaluation biases for large language models. ArXiv preprint, abs/2307.03025. find
  289. Xiang, Wei and Bang Wang. 2019. A survey of event extraction from text. IEEE Access, 7:173111–173137. find
  290. Yang, Diyi, Jiaao Chen, Zichao Yang, Dan Jurafsky, and Eduard Hovy. 2019a. Let’s make your request more persuasive: Modeling persuasive strategies via semi-supervised neural nets on crowdfunding platforms. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Com… find
  291. Yang, Diyi, Robert E. Kraut, Tenbroeck Smith, Elijah Mayfield, and Dan Jurafsky. 2019b. Seekers, providers, welcomers, and storytellers: Modeling social roles in online health communities. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019, Glasgow, Scotland, U… find
  292. Yang, Diyi, Miaomiao Wen, and Carolyn Rosé. 2015. Weakly supervised role identification in teamwork interactions. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Paper… find
  293. Yao, Yunzhi, Shaohan Huang, Wenhui Wang, Li Dong, and Furu Wei. 2021. Adapt-and-distill: Developing small, fast and effective pretrained language models for domains. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 460–470, Association for Computational Linguistic… find
  294. Yarkoni, Tal and Jacob Westfall. 2017. Choosing prediction over explanation in psychology: Lessons from machine learning. Perspectives on Psychological Science, 12(6):1100–1122. find
  295. Yu, Tao, Rui Zhang, Alex Polozov, Christopher Meek, and Ahmed Hassan Awadallah. 2021. Score: Pre-training for context representation in conversational semantic parsing. In International Conference on Learning Representations. find
  296. Yuan, Michelle, Hsuan-Tien Lin, and Jordan Boyd-Graber. 2020. Cold-start active Volume 50, Number 1 learning through self-supervised language modeling. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 7935–7948, Association for Computational Li… find
  297. Zarrella, Guido and Amy Marsh. 2016. MITRE at SemEval-2016 task 6: Transfer learning for stance detection. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pages 458–463, Association for Computational Linguistics, San Diego, California. find
  298. Zhan, Hongli, Tiberiu Sosea, Cornelia Caragea, and Junyi Jessy Li. 2022. Why do you feel this way? summarizing triggers of emotions in social media posts. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 9436–9453. find
  299. Zhang, Amy, Bryan Culbertson, and Praveen Paritosh. 2017. Characterizing online discussion using coarse discourse sequences. In Proceedings of the International AAAI Conference on Web and Social Media, volume 11, pages 357–366. find
  300. Zhang, Jing, Jie Tang, and Juanzi Li. 2007. Expert finding in a social network. In Advances in Databases: Concepts, Systems and Applications. Springer, pages 1066–1069. find
  301. Zhang, Justine, Jonathan Chang, Cristian Danescu-Niculescu-Mizil, Lucas Dixon, Yiqing Hua, Dario Taraborelli, and Nithum Thain. 2018. Conversations gone awry: Detecting early signs of conversational failure. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (… find our card
  302. Zhang, Tianyi, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020. Bertscore: Evaluating text generation with BERT. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, OpenReview.net. find
  303. Zhao, Jieyu, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018. Gender bias in coreference resolution: Evaluation and debiasing methods. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies… find our card
  304. Zhao, Zihao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021. Calibrate before use: Improving few-shot performance of language models. In International Conference on Machine Learning, pages 12697–12706, PMLR. find our card
  305. Zhou, Naitian and David Jurgens. 2020. Condolence and empathy in online communities. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 609–626, Association for Computational Linguistics, Online. find
  306. Zhu, Jian and David Jurgens. 2021a. Idiosyncratic but not arbitrary: Learning idiolects in online registers reveals distinctive yet consistent individual styles. ArXiv preprint, abs/2109.03158. find
  307. Zhu, Jian and David Jurgens. 2021b. The structure of online social networks modulates the rate of lexical change. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 2201–2218, Association for Comput… find
  308. Zhuo, Terry Yue, Yujin Huang, Chunyang Chen, and Zhenchang Xing. 2023. Exploring ai ethics of chatgpt: A diagnostic analysis. ArXiv preprint, abs/2301.12867. find
  309. Ziems, Caleb, William Held, Jingfeng Yang, Jwala Dhamala, Rahul Gupta, and Diyi Yang. 2023. Multi-VALUE: A framework for cross-dialectal English NLP. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 744–768, Association for Com… find our card
  310. Ziems, Caleb, Minzhi Li, Anthony Zhang, and Diyi Yang. 2022. Inducing positive perspectives with text reframing. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 3682–3700. find
  311. Ziems, Caleb and Diyi Yang. 2021. To protect and to serve? analyzing entity-centric framing of police violence. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 957–976. find
  312. Zong, Mingyu and Bhaskar Krishnamachari. 2022. a survey on gpt-3. find