Open AccessProceedings Article
Suspicious News Detection Using Micro Blog Text
Tsubasa Tagami,Hiroki Ouchi,Hiroki Asano,Kazuaki Hanawa,Kaori Uchiyama,Kaito Suzuki,Kentaro Inui,Atsushi Komiya,Atsuo Fujimura,Hitofumi Yanai,Ryo Yamashita,Akinori Machino +11 more
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TLDR
In this paper, the authors presented a new task, suspicious news detection using micro blog text, which aims to support human experts to detect suspicious news articles to be verified, which is costly but a crucial step before verifying the truthfulness of the articles.Abstract:
We present a new task, suspicious news detection using micro blog text. This task aims to support human experts to detect suspicious news articles to be verified, which is costly but a crucial step before verifying the truthfulness of the articles. Specifically, in this task, given a set of posts on SNS referring to a news article, the goal is to judge whether the article is to be verified or not. For this task, we create a publicly available dataset in Japanese and provide benchmark results by using several basic machine learning techniques. Experimental results show that our models can reduce the cost of manual fact-checking process.read more
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Combating Fake News in “Low-Resource” Languages: Amharic Fake News Detection Accompanied by Resource Crafting
TL;DR: In this article, a fake news detection model for low-resource African languages, such as Amharic, is presented, evaluated with the ETH_FAKE dataset and using the AMFTWE, performed very well.
Journal ArticleDOI
Detecting Suspicious Texts Using Machine Learning Techniques
TL;DR: A Machine Learning (ML)-based classification model is proposed (hereafter called STD) to classify Bengali text into non-suspicious and suspicious categories based on its original contents based onIts original contents.
Journal ArticleDOI
Certain Investigation of Fake News Detection from Facebook and Twitter Using Artificial Intelligence Approach
Roy Setiawan,Vidya Sagar Ponnam,Sudhakar Sengan,Mamoona Anam,Chidambaram Subbiah,Khongdet Phasinam,Manikandan Vairaven,Selvakumar Ponnusamy +7 more
TL;DR: Using a Machine Learning optimization technique for automated news article classification on Facebook and Twitter for social forum fake news findings in order to distort news reports from non-recurrent outlets is recommended.
Journal ArticleDOI
Suspicious news detection through semantic and sentiment measures
Alejandro Martín,Alberto Fernández-Isabel,César González-Fernández,Carmen Lancho,Marina Cuesta,Isaac Martín de Diego +5 more
TL;DR: In this article, the authors presented the Knowledge Recovering Architecture based on Keywords Extraction from Narratives for Suspicious News Detection (KRAKEN-SND) system, which supports human experts to detect suspicious news articles that should be verified.
References
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