Misogyny and Aggressiveness Tend to Come Together and Together We Address Them (2022.lrec-1)
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| Challenge: | Using a binary task to identify whether a tweet is misogynous and aggressive, we compare two approaches to address these problems: one multi-class model that discriminates between all the classes at once; and a cascaded approach where the binary classification is carried out separately. |
| Approach: | They propose a multi-class model that discriminates between all the classes at once and a cascaded approach where the binary classification is carried out separately and then joined together. |
| Outcome: | The proposed models outperform the top submissions to Evalita on the 2020 shared task on automatic misogyny and aggressiveness identification in Italian tweets. |
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| Challenge: | Online misogyny is a category of online abusive language with serious and harmful social consequences. |
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Brooklyn Sheppard, Anna Richter, Allison Cohen, Elizabeth Smith, Tamara Kneese, Carolyne Pelletier, Ioana Baldini, Yue Dong
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TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification (2020.findings-emnlp)
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| Challenge: | Modern NLP systems are typically ill-equipped when applied to noisy user-generated text. |
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