Using Neural Network for Identifying Clickbaits in Online News Media
원문 초록
Online news media sometimes use misleading headlines to lure users to open the news article. These catchy headlines that attract users but disappointed them at the end, are called Clickbaits. Because of the importance of automatic clickbait detection in online medias, lots of machine learning methods were proposed and employed to find the clickbait headlines. In this research, a model using deep learning methods is proposed to find the clickbaits in Clickbait Challenge 2017's dataset. The proposed model gained the first rank in the Clickbait Challenge 2017 in terms of Mean Squared Error. Also, data analytics and visualization techniques are employed to explore and discover the provided dataset to get more insight from the data.
함께 살펴볼 논문
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A Novel Contrastive Learning Method for Clickbait Detection on RoCliCo: A Romanian Clickbait Corpus of News Articles
Clickbait Detection via Large Language Models
A Two-Level Classification Approach for Detecting Clickbait Posts using Text-Based Features
Clickbait Detection in Tweets Using Self-attentive Network
토론
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