Fake News Detection with Semantic Features and Text Mining
نویسندگان
چکیده
منابع مشابه
Automatic Detection of Fake News
The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online...
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Social media for news consumption is becoming popular nowadays. The low cost, easy access and rapid information dissemination of social media bring benefits for people to seek out news timely. However, it also causes the widespread of fake news, i.e., low-quality news pieces that are intentionally fabricated. The fake news brings about several negative effects on individual consumers, news ecos...
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The latest election cycle generated sobering examples of the threat that fake news poses to democracy. Primarily disseminated by hyper-partisan media outlets, fake news proved capable of becoming viral sensations that can dominate social media and influence elections. To address this problem, we begin with stance detection, which is a first step towards identifying fake news. The goal of this p...
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News and blogs are two types of media that generate and offer informational resources. News is any information whose revelation is anticipated to have an intellectual or actionable impact on the recipient. The dominant type of news in text analysis is that pertaining to current events. Originally referring to print-based news from press agencies or end-user news providers (like individual newsp...
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Current text classification systems typically use term stems for representing document content. Ontologies allow the usage of features on a higher semantic level than single words for text classification purposes. In this paper we propose such an enhancement of the classical document representation through concepts extracted from background knowledge. Boosting, a successful machine learning tec...
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ژورنال
عنوان ژورنال: International Journal on Natural Language Computing
سال: 2019
ISSN: 2319-4111,2278-1307
DOI: 10.5121/ijnlc.2019.8302