# Locating Information Gaps and Narrative Inconsistencies Across Languages: A Case Study of LGBT People Portrayals on Wikipedia

arXiv: https://arxiv.org/abs/2410.04282 · HTML: https://mlsanity.com/paper/2410.04282/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 57 references that are in the map.
- First posted on arXiv 5 Oct 2024.

## Builds on (most cited first, 23 of 23)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [A large annotated corpus for learning natural language inference](https://mlsanity.com/paper/1508.05326/) (2015)
- [mT5: A massively multilingual pre-trained text-to-text transformer](https://mlsanity.com/paper/2010.11934/) (2020)
- [No Language Left Behind: Scaling Human-Centered Machine Translation](https://mlsanity.com/paper/2207.04672/) (2022)
- [FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://mlsanity.com/paper/2305.14251/) (2023)
- [ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT](https://mlsanity.com/paper/2004.12832/) (2020)
- [Language-agnostic BERT Sentence Embedding](https://mlsanity.com/paper/2007.01852/) (2020)
- [Word Translation Without Parallel Data](https://mlsanity.com/paper/1710.04087/) (2017)
- [WiCE: Real-World Entailment for Claims in Wikipedia](https://mlsanity.com/paper/2303.01432/) (2023)
- [Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings](https://mlsanity.com/paper/1811.01136/) (2018)
- [Detecting Stance in Media on Global Warming](https://mlsanity.com/paper/2010.15149/) (2020)
- [Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies](https://mlsanity.com/paper/1808.09386/) (2018)
- [It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopedia](https://mlsanity.com/paper/1501.06307/) (2015)
- [Controlled Analyses of Social Biases in Wikipedia Bios](https://mlsanity.com/paper/2101.00078/) (2020)
- [Multilingual Contextual Affective Analysis of LGBT People Portrayals in Wikipedia](https://mlsanity.com/paper/2010.10820/) (2020)
- [QUOTUS: The Structure of Political Media Coverage as Revealed by Quoting Patterns](https://mlsanity.com/paper/1504.01383/) (2015)
- [The Tower of Babel Meets Web 2.0: User-Generated Content and its Applications in a Multilingual Context](https://mlsanity.com/paper/1904.01689/) (2019)
- [Understanding Editing Behaviors in Multilingual Wikipedia](https://mlsanity.com/paper/1508.07266/) (2015)
- [Governance Capture in a Self-Governing Community: A Qualitative Comparison of the Serbo-Croatian Wikipedias](https://mlsanity.com/paper/2311.03616/) (2023)
- [Interactions of cultures and top people of Wikipedia from ranking of 24 language editions](https://mlsanity.com/paper/1405.7183/) (2014)
- [X-PARADE: Cross-Lingual Textual Entailment and Information Divergence across Paragraphs](https://mlsanity.com/paper/2309.08873/) (2023)
- [Mining cross-cultural relations from Wikipedia - A study of 31 European food cultures](https://mlsanity.com/paper/1411.4484/) (2014)

## Built on by (most cited first, 10 of 10)

- [Localizing Factual Inconsistencies in Attributable Text Generation](https://mlsanity.com/paper/2410.07473/) (2024)
- [BottleHumor: Self-Informed Humor Explanation using the Information Bottleneck Principle](https://mlsanity.com/paper/2502.18331/) (2025)
- [WikiGap: Promoting Epistemic Equity by Surfacing Knowledge Gaps Between English Wikipedia and other Language Editions](https://mlsanity.com/paper/2505.24195/) (2025)
- [Hope vs. Hate: Understanding User Interactions with LGBTQ+ News Content in Mainstream US News Media through the Lens of Hope Speech](https://mlsanity.com/paper/2502.09004/) (2025)
- [Stress Testing Factual Consistency Metrics for Long-Document Summarization](https://mlsanity.com/paper/2511.07689/) (2025)
- [CanLegalRAGBench: Evaluating Retrieval-Augmented Generation on Canadian Case Law](https://mlsanity.com/paper/2605.30497/) (2026)
- [Zoom In Disparities in Healthcare LLM Q&A](https://mlsanity.com/paper/2510.17476/) (2025)
- [Information Asymmetry across Language Varieties: A Case Study on Cantonese-Mandarin and Bavarian-German QA](https://mlsanity.com/paper/2603.14782/) (2026)
- [Convergence in Science, Divergence in Religion: Calibrated Framing Differences Across Wikipedia's Language Editions](https://mlsanity.com/paper/2608.21821/) (2026)
- [Where's Waldo? Query-language Preference under Cross-lingual Knowledge Disparities](https://mlsanity.com/paper/2610.00606/) (2026)

## Abstract (arXiv)

To explain social phenomena and identify systematic biases, much research in computational social science focuses on comparative text analyses. These studies often rely on coarse corpus-level statistics or local word-level analyses, mainly in English. We introduce the InfoGap method -- an efficient and reliable approach to locating information gaps and inconsistencies in articles at the fact level, across languages. We evaluate InfoGap by analyzing LGBT people's portrayals, across 2.7K biography pages on English, Russian, and French Wikipedias. We find large discrepancies in factual coverage across the languages. Moreover, our analysis reveals that biographical facts carrying negative connotations are more likely to be highlighted in Russian Wikipedia. Crucially, InfoGap both facilitates large scale analyses, and pinpoints local document- and fact-level information gaps, laying a new foundation for targeted and nuanced comparative language analysis at scale.