Zoom Out and Observe: News Environment Perception for Fake News
Detection
- URL: http://arxiv.org/abs/2203.10885v2
- Date: Fri, 28 Oct 2022 02:48:21 GMT
- Title: Zoom Out and Observe: News Environment Perception for Fake News
Detection
- Authors: Qiang Sheng, Juan Cao, Xueyao Zhang, Rundong Li, Danding Wang,
Yongchun Zhu
- Abstract summary: existing methods observe the language patterns of the news post and "zoom in" to verify its content.
We propose the News Environment Perception Framework (NEP) to capture the environmental signals of news posts.
Experiments on our newly built datasets show that the NEP can efficiently improve the performance of basic fake news detectors.
- Score: 18.369195554810236
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Fake news detection is crucial for preventing the dissemination of
misinformation on social media. To differentiate fake news from real ones,
existing methods observe the language patterns of the news post and "zoom in"
to verify its content with knowledge sources or check its readers' replies.
However, these methods neglect the information in the external news environment
where a fake news post is created and disseminated. The news environment
represents recent mainstream media opinion and public attention, which is an
important inspiration of fake news fabrication because fake news is often
designed to ride the wave of popular events and catch public attention with
unexpected novel content for greater exposure and spread. To capture the
environmental signals of news posts, we "zoom out" to observe the news
environment and propose the News Environment Perception Framework (NEP). For
each post, we construct its macro and micro news environment from recent
mainstream news. Then we design a popularity-oriented and a novelty-oriented
module to perceive useful signals and further assist final prediction.
Experiments on our newly built datasets show that the NEP can efficiently
improve the performance of basic fake news detectors.
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