Paula Fortuna is a distinguished professional with a diverse background in Informatics and Computing Engineering, and Social Psychology. With a PhD from Pompeu Fabra University, her research has focused on questioning practices in hate speech detection and classification, resulting in numerous publications in prestigious journals and conferences. She has also contributed to various research projects and has received several awards for her outstanding work, including research grants. With a strong technical proficiency in programming and data science, Paula Fortuna is committed to leveraging her expertise to address ethical challenges in AI and computational social science. She also actively contributes as a reviewer for prominent conferences and journals in the field.
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Selected publications:
Fortuna, P., Dominguez, M., Wanner, L., and Talat, Z. (2022). Directions for nlp practices applied to online hate speech detection. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.
Fortuna, P., Soler‐Company, J., & Wanner, L. (2021).How well do hate speech, toxicity, abusive and offensive language classification models generalize across datasets?. Information Processing & Management, 58(3), 102524.
Fortuna, P., Soler, J., & Wanner, L. (2020, May). Toxic, Hateful, Offensive or Abusive? What Are We Really Classifying? An Empirical Analysis of Hate Speech Datasets. In Proceedings of The 12th Language Resources and Evaluation Conference (pp. 6786‐6794).
Fortuna, P., da Silva, J. R., Wanner, L., & Nunes, S. (2019, August). A hierarchically‐labeled portuguese hate speech dataset. In Proceedings of the Third Workshop on Abusive Language Online (pp. 94‐104).
Fortuna, P., & Nunes, S. (2018). A Survey on Automatic Detection of Hate Speech in Text. ACM Computing Surveys (CSUR), 51(4), 85.