A Deep Learning Approach and Recurrent Neural Network Towards Clickbait Detection

“Clickbait” is a term utilized for describing headlines designed to get readers to click on a link. Some of the most popular academic methods for using convolutional and convolutional neural network. It is commonly known that deep learning approaches may be used to solve complex issues (CNN). It’s a common misconception that academic researchers looking for misleading headlines have considered the whole context of the item they’re studying. Contextual information may also help readers better comprehend a document’s content. If you want to avoid being labeled a “clickbait” title, you may want to add some context to your headline. Text classification using RCNNs takes context into consideration. Classifying advertisements using this method is common practice in online marketing, especially clickbait. LSTM and Gated Recurrent Unit improve the RCNN model’s ability to classify clickbait, making it more accurate than prior state-of-the-art (GRU) methods. Because of the prevalence of online communication and social networking tools like Facebook and Twitter, anybody with an interest in spreading misinformation may do so.