mlsanityData to 7 Oct 2026

Why Should This Article Be Deleted? Transparent Stance Detection in Multilingual Wikipedia Editor Discussions

arXiv 2310.05779 ↗First posted 9 Oct 2023cs.LG cs.CL cs.CYcited by 2

Not on the map. Why?

Abstract (arXiv)

The moderation of content on online platforms is usually non-transparent. On Wikipedia, however, this discussion is carried out publicly and the editors are encouraged to use the content moderation policies as explanations for making moderation decisions. Currently, only a few comments explicitly mention those policies -- 20% of the English ones, but as few as 2% of the German and Turkish comments. To aid in this process of understanding how content is moderated, we construct a novel multilingual dataset of Wikipedia editor discussions along with their reasoning in three languages. The dataset contains the stances of the editors (keep, delete, merge, comment), along with the stated reason, and a content moderation policy, for each edit decision. We demonstrate that stance and corresponding reason (policy) can be predicted jointly with a high degree of accuracy, adding transparency to the decision-making process. We release both our joint prediction models and the multilingual content moderation dataset for further research on automated transparent content moderation.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 10 of its 44 references that are in the map. First posted on arXiv 9 Oct 2023.

Builds on

10 of 44 references.

References · 10

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  3. 2018Datasheets for Datasetscited by 1,371
  4. 2020The State and Fate of Linguistic Diversity and Inclusion in the NLP Worldcited by 789
  5. 2020Generating Fact Checking Explanationscited by 132
  6. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  7. 2021Detecting Harmful Content On Online Platforms: What Platforms Need Vs. Where Research Efforts Gocited by 32
  8. 2021Cross-Domain Label-Adaptive Stance Detectioncited by 30
  9. 2021Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Trainingcited by 28
  10. 2022Automated Content Moderation Increases Adherence to Community Guidelinescited by 10

Built on by

Cited by year

Citing papers per year: 2024: 1; 2025: 1.

2 papers.