Editlens Scoring Data
A collection of datasets of human writing for evaluating AI-generated text detectors.
Citations:
Crossley, S. (2025). A large-scale corpus for assessing source-based writing quality: ASAP 2.0. Zenodo. https://doi.org/10.5281/zenodo.14781349
J. Schler, M. Koppel, S. Argamon and J. Pennebaker (2006). Effects of Age and Gender on Blogging in Proceedings of 2006 AAAI Spring Symposium on Computational Approaches for Analyzing Weblogs. URL: http://www.cs.biu.ac.il/~schlerj/schler_springsymp06.pdf
Blodgett, S. L., Green, L., & O’Connor, B. (2016). Demographic Dialectal Variation in Social Media: A Case Study of African-American English. In J. Su, K. Duh, & X. Carreras (Eds.), Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (pp. 1119–1130). Association for Computational Linguistics. https://doi.org/10.18653/v1/D16-1120
Blodgett, S. L., Wei, J., & O’Connor, B. (2018). Twitter Universal Dependency Parsing for African-American and Mainstream American English. In I. Gurevych & Y. Miyao (Eds.), Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 1415–1425). Association for Computational Linguistics. https://doi.org/10.18653/v1/P18-1131
Liu, Y., Qin, M. X., Wang, L., & Huang, C. (2023). CCAE: A Corpus of Chinese-Based Asian Englishes. CCF International Conference on Natural Language Processing and Chinese Computing, 614–626.
Tao Chen and Min-Yen Kan (2013). Creating a Live, Public Short Message Service Corpus: The NUS SMS Corpus. Language Resources and Evaluation, 47(2)(2013), pages 299-355. URL: https://link.springer.com/article/10.1007%2Fs10579-012-9197-9
Crossley, S. A., Tian, Y., Baffour, P., Franklin, A., Benner, M., & Boser, U. (2024). A large-scale corpus for assessing written argumentation: PERSUADE 2.0. Assessing Writing, 61, 100865. https://doi.org/10.1016/j.asw.2024.100865