# Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder

arXiv: https://arxiv.org/abs/1811.07066 · HTML: https://mlsanity.com/paper/1811.07066/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Nov 2018.

## Built on by (most cited first, 15 of 15)

- [PASTA: Table-Operations Aware Fact Verification via Sentence-Table Cloze Pre-training](https://mlsanity.com/paper/2211.02816/) (2022)
- [MSynFD: Multi-hop Syntax aware Fake News Detection](https://mlsanity.com/paper/2402.14834/) (2024)
- [Table-based Fact Verification with Salience-aware Learning](https://mlsanity.com/paper/2109.04053/) (2021)
- [Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text](https://mlsanity.com/paper/2106.01033/) (2021)
- [Clickbait Detection via Large Language Models](https://mlsanity.com/paper/2306.09597/) (2023)
- [Graph with Sequence: Broad-Range Semantic Modeling for Fake News Detection](https://mlsanity.com/paper/2412.05672/) (2024)
- [Prompt-tuning for Clickbait Detection via Text Summarization](https://mlsanity.com/paper/2404.11206/) (2024)
- [Emulating Reader Behaviors for Fake News Detection](https://mlsanity.com/paper/2306.15231/) (2023)
- [Fake News Detection Tools and Methods -- A Review](https://mlsanity.com/paper/2112.11185/) (2021)
- [Incongruity Detection between Bangla News Headline and Body Content through Graph Neural Network](https://mlsanity.com/paper/2211.07709/) (2022)
- [Exploring the Potential of the Large Language Models (LLMs) in Identifying Misleading News Headlines](https://mlsanity.com/paper/2405.03153/) (2024)
- [Journalism-Guided Agentic In-Context Learning for News Stance Detection](https://mlsanity.com/paper/2507.11049/) (2025)
- [POSHAN: Cardinal POS Pattern Guided Attention for News Headline Incongruence](https://mlsanity.com/paper/2111.03547/) (2021)
- [How does fake news use a thumbnail? CLIP-based Multimodal Detection on the Unrepresentative News Image](https://mlsanity.com/paper/2204.05533/) (2022)
- [ClickGuard: A Trustworthy Adaptive Fusion Framework for Clickbait Detection](https://mlsanity.com/paper/2604.07272/) (2026)

## Abstract (arXiv)

Some news headlines mislead readers with overrated or false information, and identifying them in advance will better assist readers in choosing proper news stories to consume. This research introduces million-scale pairs of news headline and body text dataset with incongruity label, which can uniquely be utilized for detecting news stories with misleading headlines. On this dataset, we develop two neural networks with hierarchical architectures that model a complex textual representation of news articles and measure the incongruity between the headline and the body text. We also present a data augmentation method that dramatically reduces the text input size a model handles by independently investigating each paragraph of news stories, which further boosts the performance. Our experiments and qualitative evaluations demonstrate that the proposed methods outperform existing approaches and efficiently detect news stories with misleading headlines in the real world.