[ASONAM 2019] Synthetic Texts (clickbaits) Generation using Different Variations of VAE. Code for paper "5 Sources of Clickbaits You Should Know! Using Synthetic Clickbaits to Improve Prediction and Distinguish between Bot-Generated and Human-Written Headlines"
A machine learning driven Clickbait classifier.
A chat server and cleint using python and the google drive API.
A proof of concept, combining the submissions to the ClickbaitChallenge2017 into a meta machine learning model.
Project aims to detect clickbaits by extracting various features from each part of article/post. Code for Clickbait Challenge Competition.
A Naive Bayes classifier to detect clickbait headlines
[CSCWD'23] Detecting Clickbait in Chinese Social Media by Prompt Learning
Generating Clickbait Titles with Machine Learning
Automatic clickbait detection and content extraction in social media.
This repository represent an AI method to classify an article as clickbait or non-clickbait
Better youtube recommendations
Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue
Deep learning models to identify clickbaits taking content into consideration
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