TieFake: Title-Text Similarity and Emotion-Aware Fake News Detection

Understand

Fake news detection aims to detect fake news widely spreading on social media platforms, which can negatively influence the public and the government.

• Many approaches have been developed to exploit relevant information from news images, text, or videos.
• However, these methods may suffer from the following limitations: (1) ignore the inherent emotional information of the news, which could be beneficial since it contains the subjective intentions of the authors; (2) pay little attention to the relation (similarity) between the title and textual information in news articles, which often use irrelevant title to attract reader' attention.
• To this end, we propose a novel Title-Text similarity and emotion-aware Fake news detection (TieFake) method by jointly modeling the multi-modal context information and the author sentiment in a unified framework.