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Many NLP applications require manual data annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models.
“What Determines Inter-Coder Agreement in Manual Annotations? A Meta-Analytic Investigation.” Computational Linguistics
Bayerl, Petra Saskia and Karsten Ingmar Paul. 2011 · 2011
Earlier work this paper cites.
The media frames corpus: Annotations of frames across issues. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
Card, Dallas, Amber Boydstun, Justin H Gross, Philip Resnik and Noah A Smith. 2015 · 2015
Earlier work this paper cites.
“Crowd-Sourced Text Analysis: Reproducible and Agile Production of Political Data.” American Political Science Review
Benoit, Kenneth, Drew Conway, Benjamin E. Lauderdale, Michael Laver and Slava Mikhaylov. 2016 · 2016
Earlier work this paper cites.
“An MTurk Crisis? Shifts in Data Quality and the Impact on Study Results.” Social Psychological and Personality Science
Chmielewski, Michael and Sarah C. Kucker. 2020 · 2020
Earlier work this paper cites.
Semi-automated data labeling. In NeurIPS 2020 Competition and Demonstration Track
Desmond, Michael, Evelyn Duesterwald, Kristina Brimijoin, Michelle Brachman and Qian Pan. 2021 · 2020
Earlier work this paper cites.
“Content Moderation As a Political Issue: The Twitter Discourse Around Trump’s Ban.” Journal of Quantitative Description: Digital Media
Alizadeh, Meysam, Fabrizio Gilardi, Emma Hoes, K Jonathan Klüser, Mael Kubli and Nahema Marchal. 2022 · 2022
Cited alongside, same era.
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Emerson, Guy, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh and Shyam Ratan, eds. 2022 · 2022
Cited alongside, same era.
“Large language models are zero-shot reasoners.” arXiv preprint arXiv:2205.11916
Kojima, Takeshi, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
“Out of One, Many: Using Language Models to Simulate Human Samples.” Political Analysis
Argyle, Lisa P., Ethan C. Busby, Nancy Fulda, Joshua R. Gubler, Christopher Rytting and David Wingate. 2023 · 2023
Cited alongside, same era.
“Using cognitive psychology to understand GPT-3.” Proceedings of the National Academy of Sciences
Huang, Fan, Haewoon Kwak and Jisun An. 2023 · 2023
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“ChatGPT: Beginning of an End of Manual Linguistic Data Annotation? Use Case of Automatic Genre Identification.” arXiv e-prints
Kuzman, Taja, Igor Mozetič and Nikola Ljubešić. 2023 · 2023
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“Large Language Models as Corporate Lobbyists.”
Nay, John J. 2023 · 2023
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“Large Language Models Can Be Used to Estimate the Ideologies of Politicians in a Zero-Shot Learning Setting.”
Wu, Patrick Y., Joshua A. Tucker, Jonathan Nagler and Solomon Messing. 2023 · 2023
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Binz, Marcel and Eric Schulz. 2023 · 2023
Cited alongside, same era.