# Rumor Detection on Social Media: Datasets, Methods and Opportunities

arXiv: https://arxiv.org/abs/1911.07199 · HTML: https://mlsanity.com/paper/1911.07199/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Nov 2019.

## Built on by (most cited first, 8 of 8)

- [Can LLM-Generated Misinformation Be Detected?](https://mlsanity.com/paper/2309.13788/) (2023)
- [Misinformation Detection on YouTube Using Video Captions](https://mlsanity.com/paper/2107.00941/) (2021)
- [A Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learning](https://mlsanity.com/paper/2204.02626/) (2022)
- [Explicit, Implicit, and Scattered: Revisiting Event Extraction to Capture Complex Arguments](https://mlsanity.com/paper/2410.03594/) (2024)
- [Discourse Structures Guided Fine-grained Propaganda Identification](https://mlsanity.com/paper/2310.18544/) (2023)
- [Event Detection from Social Media Stream: Methods, Datasets and Opportunities](https://mlsanity.com/paper/2306.16495/) (2023)
- [Rumour detection using graph neural network and oversampling in benchmark Twitter dataset](https://mlsanity.com/paper/2212.10080/) (2022)
- [Detecting Rumor Veracity with Only Textual Information by Double-Channel Structure](https://mlsanity.com/paper/2312.03195/) (2023)

## Abstract (arXiv)

Social media platforms have been used for information and news gathering, and they are very valuable in many applications. However, they also lead to the spreading of rumors and fake news. Many efforts have been taken to detect and debunk rumors on social media by analyzing their content and social context using machine learning techniques. This paper gives an overview of the recent studies in the rumor detection field. It provides a comprehensive list of datasets used for rumor detection, and reviews the important studies based on what types of information they exploit and the approaches they take. And more importantly, we also present several new directions for future research.