paper-with-me

홈 › Papers

LTCR: Long-Text Chinese Rumor Detection Dataset

2023-06-12 · Ziyang Ma, Mengsha Liu, Guian Fang, Ying Shen

False information can spread quickly on social media, negatively influencing the citizens' behaviors and responses to social events. To better detect all of the fake news, especially long texts which are harder to find completely, a Long-Text Chinese Rumor detection dataset named LTCR is proposed. The LTCR dataset provides a valuable resource for accurately detecting misinformation, especially in the context of complex fake news related to COVID-19. The dataset consists of 1,729 and 500 pieces of real and fake news, respectively. The average lengths of real and fake news are approximately 230 and 152 characters. We also propose \method, Salience-aware Fake News Detection Model, which achieves the highest accuracy (95.85%), fake news recall (90.91%) and F-score (90.60%) on the dataset. (https://github.com/Enderfga/DoubleCheck)

📄 PDF Abstract BibTeX arXiv:2306.07201

Code (1)

enderfga/doublecheck 공식 구현 pytorch

Tasks

Fake News DetectionMisinformation

Similar Papers 제목 키워드 기반

HRDE: Retrieval-Augmented Large Language Models for Chinese Health Rumor Detection and Explainability

2024-06-30 · Yanfang Chen, Ding Chen, Shichao Song, Simin Niu 외

As people increasingly prioritize their health, the speed and breadth of health information dissemination on the internet have also grown. At the same time, the presence of false health information (health rumors) interm…

Retrieval

RAGAT-Mind: A Multi-Granular Modeling Approach for Rumor Detection Based on MindSpore

2025-04-24 · Zhenkai Qin, Guifang Yang, Dongze Wu

As false information continues to proliferate across social media platforms, effective rumor detection has emerged as a pressing challenge in natural language processing. This paper proposes RAGAT-Mind, a multi-granular …

STANKER: Stacking Network based on Level-grained Attention-masked BERT for Rumor Detection on Social Media

2021-11-01 · EMNLP 2021 11 · Dongning Rao, Xin Miao, Zhihua Jiang, Ran Li

Rumor detection on social media puts pre-trained language models (LMs), such as BERT, and auxiliary features, such as comments, into use. However, on the one hand, rumor detection datasets in Chinese companies with comme…

Call Attention to Rumors: Deep Attention Based Recurrent Neural Networks for Early Rumor Detection

2017-04-20 · Tong Chen, Lin Wu, Xue Li, Jun Zhang 외

The proliferation of social media in communication and information dissemination has made it an ideal platform for spreading rumors. Automatically debunking rumors at their stage of diffusion is known as \textit{early ru…

Deep Attention

Toward Effective Multi-Domain Rumor Detection in Social Networks Using Domain-Gated Mixture-of-Experts

2026-01-28 · Mohadeseh Sheikhqoraei, Zainabolhoda Heshmati, Zeinab Rajabi, Leila Rabiei arxiv

Social media platforms have become key channels for spreading and tracking rumors due to their widespread accessibility and ease of information sharing. Rumors can continuously emerge across diverse domains and topics, o…