Using Neural Network for Identifying Clickbaits in Online News Media
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Jun 2018.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 0; 2025: 2.
5 papers.
- 2021On Unifying Misinformation Detectioncited by 10
- 2021SOK: Fake News Outbreak 2021: Can We Stop the Viral Spread?cited by 0
- 2021Is it a click bait? Let's predict using Machine Learningcited by 0
- 2025Te Ahorr'e Un Click: A Revised Definition of Clickbait and Detection in Spanish Newscited by 0
- 2025SmartMixed: A Two-Phase Training Strategy for Adaptive Activation Function Learning in Neural Networkscited by 0
- 2025SmartMixed: A Two-Phase Training Strategy for Adaptive Activation Function Learning in Neural Networks25 Oct 2025
- 2025Te Ahorr'e Un Click: A Revised Definition of Clickbait and Detection in Spanish News13 Jul 2025
- 2021Is it a click bait? Let's predict using Machine Learning1 Jun 2021
- 2021SOK: Fake News Outbreak 2021: Can We Stop the Viral Spread?22 May 2021
- 2021On Unifying Misinformation Detection12 Apr 2021