About

Clickbait detection is the task of identifying clickbait, a form of false advertisement, that uses hyperlink text or a thumbnail link that is designed to attract attention and to entice users to follow that link and read, view, or listen to the linked piece of online content, with a defining characteristic of being deceptive, typically sensationalized or misleading (Source: Adapted from Wikipedia)

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Greatest papers with code

We used Neural Networks to Detect Clickbaits: You won't believe what happened Next!

5 Dec 2016ankeshanand/deep-clickbait-detection

Online content publishers often use catchy headlines for their articles in order to attract users to their websites.

CLICKBAIT DETECTION FEATURE ENGINEERING

Clickbait Detection in Tweets Using Self-attentive Network

15 Oct 2017zhouyiwei/cc

Clickbait detection in tweets remains an elusive challenge.

CLICKBAIT DETECTION FEATURE ENGINEERING

A Two-Level Classification Approach for Detecting Clickbait Posts using Text-Based Features

23 Oct 2017clickbait-challenge/snapper

The detector is based almost exclusively on text-based features taken from previous work on clickbait detection, our own work on fake post detection, and features we designed specifically for the challenge.

CLICKBAIT DETECTION FAKE NEWS DETECTION FEATURE SELECTION

Using Neural Network for Identifying Clickbaits in Online News Media

20 Jun 2018tanamania5555/InstaAsli

Online news media sometimes use misleading headlines to lure users to open the news article.

CLICKBAIT DETECTION