Rumor Detection on Social Media: Datasets, Methods and Opportunities

November 17, 2019 Β· Declared Dead Β· πŸ› Conference on Empirical Methods in Natural Language Processing

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Quanzhi Li, Qiong Zhang, Luo Si, Yingchi Liu arXiv ID 1911.07199 Category cs.IR: Information Retrieval Cross-listed cs.CL, cs.CY, cs.SI Citations 58 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 3 months ago
Abstract
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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Information Retrieval

Died the same way β€” πŸ‘» Ghosted