# Check News in One Click: NLP-Empowered Pro-Kremlin Propaganda Detection

arXiv: https://arxiv.org/abs/2401.15717 · HTML: https://mlsanity.com/paper/2401.15717/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 23 references that are in the map.
- First posted on arXiv 28 Jan 2024.

## Builds on (most cited first, 7 of 7)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Defending Against Neural Fake News](https://mlsanity.com/paper/1905.12616/) (2019)
- [Prta: A System to Support the Analysis of Propaganda Techniques in the News](https://mlsanity.com/paper/2005.05854/) (2020)
- [Proppy: A System to Unmask Propaganda in Online News](https://mlsanity.com/paper/1912.06810/) (2019)
- [Russian propaganda on social media during the 2022 invasion of Ukraine](https://mlsanity.com/paper/2211.04154/) (2022)
- [Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classification](https://mlsanity.com/paper/2209.13017/) (2022)
- [Automated multilingual detection of Pro-Kremlin propaganda in newspapers and Telegram posts](https://mlsanity.com/paper/2301.10604/) (2023)

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

- [The FIGNEWS Shared Task on News Media Narratives](https://mlsanity.com/paper/2407.18147/) (2024)
- [MisinfoTeleGraph: Network-driven Misinformation Detection for German Telegram Messages](https://mlsanity.com/paper/2506.22529/) (2025)
- [Multiperspectivity as a Resource for Narrative Similarity Prediction](https://mlsanity.com/paper/2603.22103/) (2026)
- [XplaiNLP at CheckThat! 2025: Multilingual Subjectivity Detection with Finetuned Transformers and Prompt-Based Inference with Large Language Models](https://mlsanity.com/paper/2509.12130/) (2025)
- [Fine-tuning with Hierarchical Prompting for Robust Propaganda Classification Across Annotation Schemas](https://mlsanity.com/paper/2605.13663/) (2026)

## Abstract (arXiv)

Many European citizens become targets of the Kremlin propaganda campaigns, aiming to minimise public support for Ukraine, foster a climate of mistrust and disunity, and shape elections (Meister, 2022). To address this challenge, we developed ''Check News in 1 Click'', the first NLP-empowered pro-Kremlin propaganda detection application available in 7 languages, which provides the lay user with feedback on their news, and explains manipulative linguistic features and keywords. We conducted a user study, analysed user entries and models' behaviour paired with questionnaire answers, and investigated the advantages and disadvantages of the proposed interpretative solution.