Abstract
Detecting fake news on social media is an urgent task. Some early studies focus on capturing authenticity information from news content, while the single information source results in limited clues. Recent studies have great concern about more clues derived from auxiliary knowledge, yet it is usually rare at the early stage of news propagation. Furthermore, such studies, with more attention on the intra-news properties of individual news, would impair the performance on newly emerged events. To alleviate these issues, we propose a novel Inter-News Relation Mining (INRM) framework to mine inter-news relations. Whether for scenarios with little auxiliary knowledge or newly emerged events, INRM can provide more effective credibility clues for verifying th e truth of news. Experiments illustrate that INRM outperforms state-of-the-art methods on both conventional tasks and newly emerged event tasks.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
