Papers by Paula Fortuna

2 papers
Toxic, Hateful, Offensive or Abusive? What Are We Really Classifying? An Empirical Analysis of Hate Speech Datasets (2020.lrec-1)

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Challenge: a recent study shows that many definitions are being used for equivalent concepts, making most datasets incompatible.
Approach: They analyze six publicly available datasets to determine their similarity and compatibility . they propose to use Fast Text word vectors to analyze similarity between different datasets .
Outcome: The proposed model performs better on similar datasets and worse on more non-offensive samples.
Directions for NLP Practices Applied to Online Hate Speech Detection (2022.emnlp-main)

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Challenge: Existing approaches to address hate speech in online spaces have relied on conventions and practices from NLP.
Approach: They argue that many conventions in NLP are poorly suited for the problem and encourage researchers to develop methods that are more appropriate for the task.
Outcome: The proposed methods are poorly suited for the problem and should be adapted to address the propagation of online harms.

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