# Cultural Compass: Predicting Transfer Learning Success in Offensive Language Detection with Cultural Features

arXiv: https://arxiv.org/abs/2310.06458 · HTML: https://mlsanity.com/paper/2310.06458/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 34 of its 69 references that are in the map.
- First posted on arXiv 10 Oct 2023.

## Builds on (most cited first, 30 of 34)

- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [How multilingual is Multilingual BERT?](https://mlsanity.com/paper/1906.01502/) (2019)
- [Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT](https://mlsanity.com/paper/1904.09077/) (2019)
- [Predicting the Type and Target of Offensive Posts in Social Media](https://mlsanity.com/paper/1902.09666/) (2019)
- [Challenges and Strategies in Cross-Cultural NLP](https://mlsanity.com/paper/2203.10020/) (2022)
- [Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study](https://mlsanity.com/paper/2303.17466/) (2023)
- [Emerging Cross-lingual Structure in Pretrained Language Models](https://mlsanity.com/paper/1911.01464/) (2019)
- [Choosing Transfer Languages for Cross-Lingual Learning](https://mlsanity.com/paper/1905.12688/) (2019)
- [NLPositionality: Characterizing Design Biases of Datasets and Models](https://mlsanity.com/paper/2306.01943/) (2023)
- [COLD: A Benchmark for Chinese Offensive Language Detection](https://mlsanity.com/paper/2201.06025/) (2022)
- [Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion](https://mlsanity.com/paper/1804.07745/) (2018)
- [Offensive Language and Hate Speech Detection for Danish](https://mlsanity.com/paper/1908.04531/) (2019)
- [Handling and Presenting Harmful Text in NLP Research](https://mlsanity.com/paper/2204.14256/) (2022)
- [Learning Language Representations for Typology Prediction](https://mlsanity.com/paper/1707.09569/) (2017)
- [Overview of the HASOC track at FIRE 2020: Hate Speech and Offensive Content Identification in Indo-European Languages](https://mlsanity.com/paper/2108.05927/) (2021)
- [MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition](https://mlsanity.com/paper/2210.12391/) (2022)
- [Detecting Cross-Geographic Biases in Toxicity Modeling on Social Media](https://mlsanity.com/paper/2104.06999/) (2021)
- [Arabic Offensive Language on Twitter: Analysis and Experiments](https://mlsanity.com/paper/2004.02192/) (2020)
- [Overlap-based Vocabulary Generation Improves Cross-lingual Transfer Among Related Languages](https://mlsanity.com/paper/2203.01976/) (2022)
- [Predicting the Performance of Multilingual NLP Models](https://mlsanity.com/paper/2110.08875/) (2021)
- [Cross-Cultural Transfer Learning for Chinese Offensive Language Detection](https://mlsanity.com/paper/2303.17927/) (2023)
- [Multi Task Learning For Zero Shot Performance Prediction of Multilingual Models](https://mlsanity.com/paper/2205.06130/) (2022)
- [Unsupervised Hyperalignment for Multilingual Word Embeddings](https://mlsanity.com/paper/1811.01124/) (2018)
- [Zero-shot Dependency Parsing with Pre-trained Multilingual Sentence Representations](https://mlsanity.com/paper/1910.05479/) (2019)
- [Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set](https://mlsanity.com/paper/1909.01522/) (2019)
- [Analysing The Impact Of Linguistic Features On Cross-Lingual Transfer](https://mlsanity.com/paper/2105.05975/) (2021)
- [KOLD: Korean Offensive Language Dataset](https://mlsanity.com/paper/2205.11315/) (2022)
- [Distant Supervision from Disparate Sources for Low-Resource Part-of-Speech Tagging](https://mlsanity.com/paper/1808.09733/) (2018)
- [Transfer Language Selection for Zero-Shot Cross-Lingual Abusive Language Detection](https://mlsanity.com/paper/2206.00962/) (2022)
- [EnCBP: A New Benchmark Dataset for Finer-Grained Cultural Background Prediction in English](https://mlsanity.com/paper/2203.14498/) (2022)

## Built on by (most cited first, 18 of 18)

- [Towards Measuring and Modeling "Culture" in LLMs: A Survey](https://mlsanity.com/paper/2403.15412/) (2024)
- [Culture is Not Trivia: Sociocultural Theory for Cultural NLP](https://mlsanity.com/paper/2502.12057/) (2025)
- [Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art](https://mlsanity.com/paper/2406.03930/) (2024)
- [Extrinsic Evaluation of Cultural Competence in Large Language Models](https://mlsanity.com/paper/2406.11565/) (2024)
- [Cultural Conditioning or Placebo? On the Effectiveness of Socio-Demographic Prompting](https://mlsanity.com/paper/2406.11661/) (2024)
- [Diffusion Models Through a Global Lens: Are They Culturally Inclusive?](https://mlsanity.com/paper/2502.08914/) (2025)
- [Does Cross-Cultural Alignment Change the Commonsense Morality of Language Models?](https://mlsanity.com/paper/2406.16316/) (2024)
- [Susu Box or Piggy Bank: Assessing Cultural Commonsense Knowledge between Ghana and the U.S](https://mlsanity.com/paper/2410.16451/) (2024)
- [Cultural Adaptation of Recipes](https://mlsanity.com/paper/2310.17353/) (2023)
- [Bhaasha, Bhasa, Zaban: A Survey for Low-Resourced Languages in South Asia -- Current Stage and Challenges](https://mlsanity.com/paper/2509.11570/) (2025)
- [Self-Explaining Hate Speech Detection with Moral Rationales](https://mlsanity.com/paper/2601.03481/) (2026)
- [Don't Erase, Inform! Detecting and Contextualizing Harmful Language in Cultural Heritage Collections](https://mlsanity.com/paper/2505.24538/) (2025)
- [Culture Matters in Toxic Language Detection in Persian](https://mlsanity.com/paper/2506.03458/) (2025)
- [Do Large Language Models Know Folktales? A Case Study of Yokai in Japanese Folktales](https://mlsanity.com/paper/2506.03619/) (2025)
- [RusCode: Russian Cultural Code Benchmark for Text-to-Image Generation](https://mlsanity.com/paper/2502.07455/) (2025)
- [Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook](https://mlsanity.com/paper/2604.06210/) (2026)
- [CRAFT: Cultural Russian-Oriented Dataset Adaptation for Focused Text-to-Image Generation](https://mlsanity.com/paper/2505.04851/) (2025)
- [CultureMINE: Datasets and Methods for Improving the Cultural Capabilities of NLP Systems](https://mlsanity.com/paper/2609.22494/) (2026)

## Abstract (arXiv)

The increasing ubiquity of language technology necessitates a shift towards considering cultural diversity in the machine learning realm, particularly for subjective tasks that rely heavily on cultural nuances, such as Offensive Language Detection (OLD). Current understanding underscores that these tasks are substantially influenced by cultural values, however, a notable gap exists in determining if cultural features can accurately predict the success of cross-cultural transfer learning for such subjective tasks. Addressing this, our study delves into the intersection of cultural features and transfer learning effectiveness. The findings reveal that cultural value surveys indeed possess a predictive power for cross-cultural transfer learning success in OLD tasks and that it can be further improved using offensive word distance. Based on these results, we advocate for the integration of cultural information into datasets. Additionally, we recommend leveraging data sources rich in cultural information, such as surveys, to enhance cultural adaptability. Our research signifies a step forward in the quest for more inclusive, culturally sensitive language technologies.