mlsanityData to 14 Oct 2026

When a Language Question Is at Stake. A Revisited Approach to Label Sensitive Content

arXiv 2311.10514 ↗First posted 17 Nov 2023cs.CLcited by 0

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Abstract (arXiv)

Many under-resourced languages require high-quality datasets for specific tasks such as offensive language detection, disinformation, or misinformation identification. However, the intricacies of the content may have a detrimental effect on the annotators. The article aims to revisit an approach of pseudo-labeling sensitive data on the example of Ukrainian tweets covering the Russian-Ukrainian war. Nowadays, this acute topic is in the spotlight of various language manipulations that cause numerous disinformation and profanity on social media platforms. The conducted experiment highlights three main stages of data annotation and underlines the main obstacles during machine annotation. Ultimately, we provide a fundamental statistical analysis of the obtained data, evaluation of models used for pseudo-labelling, and set further guidelines on how the scientists can leverage the corpus to execute more advanced research and extend the existing data samples without annotators' engagement.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 45 references that are in the map. First posted on arXiv 17 Nov 2023.

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References · 11

  1. 2019Self-training with Noisy Student improves ImageNet classificationcited by 1,311
  2. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 736
  3. 2019Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learningcited by 510
  4. 2019Label Propagation for Deep Semi-supervised Learningcited by 289
  5. 2019Predicting the Type and Target of Offensive Posts in Social Mediacited by 271
  6. 2017Understanding Abuse: A Typology of Abusive Language Detection Subtaskscited by 116
  7. 2017Measuring the Reliability of Hate Speech Annotations: The Case of the European Refugee Crisiscited by 96
  8. 2021WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language modelscited by 89
  9. 2019Offensive Language and Hate Speech Detection for Danishcited by 49
  10. 2022Challenges and Opportunities in Information Manipulation Detection: An Examination of Wartime Russian Mediacited by 10
  11. 2022Enriching Abusive Language Detection with Community Contextcited by 3

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