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We present a new task, suspicious news detection using micro blog text. Thistask aims to support human experts to detect suspicious news articles to beverified, which is costly but a crucial step before verifying the truthfulnessof the articles. Specifically, in this task, given a set of posts on SNSreferring to a news article, the goal is to judge whether the article is to beverified or not. For this task, we create a publicly available dataset inJapanese and provide benchmark results by using several basic machine learningtechniques. Experimental results show that our models can reduce the cost ofmanual fact-checking process.

Suspicious News Detection Using Micro Blog Text