# UKElectionNarratives: A Dataset of Misleading Narratives Surrounding Recent UK General Elections

arXiv: https://arxiv.org/abs/2505.05459 · HTML: https://mlsanity.com/paper/2505.05459/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 109 references that are in the map.
- First posted on arXiv 8 May 2025.

## Builds on (most cited first, 12 of 12)

- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Gemma 2: Improving Open Language Models at a Practical Size](https://mlsanity.com/paper/2408.00118/) (2024)
- [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018)
- [BERTopic: Neural topic modeling with a class-based TF-IDF procedure](https://mlsanity.com/paper/2203.05794/) (2022)
- [Towards General Text Embeddings with Multi-stage Contrastive Learning](https://mlsanity.com/paper/2308.03281/) (2023)
- [Fine-Grained Analysis of Propaganda in News Articles](https://mlsanity.com/paper/1910.02517/) (2019)
- [RumourEval 2019: Determining Rumour Veracity and Support for Rumours](https://mlsanity.com/paper/1809.06683/) (2018)
- [Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election](https://mlsanity.com/paper/1707.00086/) (2017)
- [Don't Waste a Single Annotation: Improving Single-Label Classifiers Through Soft Labels](https://mlsanity.com/paper/2311.05265/) (2023)
- [Stanceosaurus: Classifying Stance Towards Multilingual Misinformation](https://mlsanity.com/paper/2210.15954/) (2022)
- [Detecting Propaganda Techniques in Code-Switched Social Media Text](https://mlsanity.com/paper/2305.14534/) (2023)

## Built on by (most cited first, 5 of 5)

- [Retrieving Climate Change Disinformation by Narrative](https://mlsanity.com/paper/2603.22015/) (2026)
- [Infini-News: Efficiently Queryable Access to 1.3 Billion Processed Common Crawl News Articles](https://mlsanity.com/paper/2605.18337/) (2026)
- [LLM-based Detection of Manipulative Political Narratives](https://mlsanity.com/paper/2605.14354/) (2026)
- [MigrationNarrate: A Dataset for Detection of Migration Narratives in YouTube Videos](https://mlsanity.com/paper/2608.20984/) (2026)
- [From Repetition to Recognition: Inductive Discovery of Disinformation Narratives](https://mlsanity.com/paper/2609.11128/) (2026)

## Abstract (arXiv)

Misleading narratives play a crucial role in shaping public opinion during elections, as they can influence how voters perceive candidates and political parties. This entails the need to detect these narratives accurately. To address this, we introduce the first taxonomy of common misleading narratives that circulated during recent elections in Europe. Based on this taxonomy, we construct and analyse UKElectionNarratives: the first dataset of human-annotated misleading narratives which circulated during the UK General Elections in 2019 and 2024. We also benchmark Pre-trained and Large Language Models (focusing on GPT-4o), studying their effectiveness in detecting election-related misleading narratives. Finally, we discuss potential use cases and make recommendations for future research directions using the proposed codebook and dataset.