Towards reliable online clickbait video detection: A content-agnostic approach

Volume: 182, Pages: 104851 - 104851
Published: Oct 1, 2019
Abstract
Online video sharing platforms (e.g., YouTube, Vimeo) have become an increasingly popular paradigm for people to consume video contents. Clickbait video, whose content clearly deviates from its title/thumbnail, has emerged as a critical problem on online video sharing platforms. Current clickbait detection solutions that mainly focus on analyzing the text of the title, the image of the thumbnail, or the content of the video are shown to be...
Paper Details
Title
Towards reliable online clickbait video detection: A content-agnostic approach
Published Date
Oct 1, 2019
Journal
Volume
182
Pages
104851 - 104851
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