Diving Deep into Clickbaits: Who Use Them to What Extents in Which Topics with What Effects?
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Abstract (arXiv)
The use of alluring headlines (clickbait) to tempt the readers has become a growing practice nowadays. For the sake of existence in the highly competitive media industry, most of the on-line media including the mainstream ones, have started following this practice. Although the wide-spread practice of clickbait makes the reader's reliability on media vulnerable, a large scale analysis to reveal this fact is still absent. In this paper, we analyze 1.67 million Facebook posts created by 153 media organizations to understand the extent of clickbait practice, its impact and user engagement by using our own developed clickbait detection model. The model uses distributed sub-word embeddings learned from a large corpus. The accuracy of the model is 98.3%. Powered with this model, we further study the distribution of topics in clickbait and non-clickbait contents.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Mar 2017.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 3; 2024: 3; 2025: 1; 2026: 1.
11 papers.
- 2022Clickbait Spoiling via Question Answering and Passage Retrievalcited by 9
- 2021SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checkingcited by 8
- 2024Multimodal Clickbait Detection by De-confounding Biases Using Causal Representation Inferencecited by 6
- 2023Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlinescited by 5
- 2023Clickbait Detection via Large Language Modelscited by 4
- 2024Prompt-tuning for Clickbait Detection via Text Summarizationcited by 3
- 2024What Drives Online Popularity: Author, Content or Sharers? Estimating Spread Dynamics with Bayesian Mixture Hawkescited by 2
- 2023BanglaBait: Semi-Supervised Adversarial Approach for Clickbait Detection on Bangla Clickbait Datasetcited by 1
- 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
- 2026Emotion-Aware Clickbait Attack in Social Mediacited by 0
- 2026Emotion-Aware Clickbait Attack in Social Media30 Apr 2026
- 2025Te Ahorr'e Un Click: A Revised Definition of Clickbait and Detection in Spanish News13 Jul 2025
- 2024Multimodal Clickbait Detection by De-confounding Biases Using Causal Representation Inference10 Oct 2024
- 2024What Drives Online Popularity: Author, Content or Sharers? Estimating Spread Dynamics with Bayesian Mixture Hawkes5 Jun 2024
- 2024Prompt-tuning for Clickbait Detection via Text Summarization17 Apr 2024
- 2023BanglaBait: Semi-Supervised Adversarial Approach for Clickbait Detection on Bangla Clickbait Dataset10 Nov 2023
- 2023Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlines20 Oct 2023
- 2023Clickbait Detection via Large Language Models16 Jun 2023
- 2022Clickbait Spoiling via Question Answering and Passage Retrieval19 Mar 2022
- 2021SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking25 Oct 2021
- 2021Is it a click bait? Let's predict using Machine Learning1 Jun 2021