{"url":"/task/clickbait-detection","name":"Clickbait Detection","slug":"clickbait-detection","description_markdown":"Clickbait detection is the task of identifying clickbait, a form of false advertisement, that uses hyperlink text or a thumbnail link that is designed to attract attention and to entice users to follow that link and read, view, or listen to the linked piece of online content, with a defining characteristic of being deceptive, typically sensationalized or misleading (Source: Adapted from Wikipedia)","categories":[{"name":"Natural Language Processing","url":"/area/natural-language-processing"},{"name":"Playing Games","url":"/area/playing-games"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"derived"},"counts":{"papers_tagged":31,"papers_with_code":9,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":0,"subtasks":0,"parent_tasks":0},"benchmarks":[],"datasets":[],"subtasks":[],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":9,"of":9,"tagged_in_all":31,"items":[{"url":"/paper/using-neural-network-for-identifying","title":"Using Neural Network for Identifying Clickbaits in Online News Media","date":"2018-06-20","arxiv_id":"1806.07713","repositories_listed":2,"syntology":null},{"url":"/paper/we-used-neural-networks-to-detect-clickbaits","title":"We used Neural Networks to Detect Clickbaits: You won't believe what happened Next!","date":"2016-12-05","arxiv_id":"1612.01340","repositories_listed":2,"syntology":null},{"url":"/paper/banglabait-semi-supervised-adversarial","title":"BanglaBait: Semi-Supervised Adversarial Approach for Clickbait Detection on Bangla Clickbait Dataset","date":"2023-11-10","arxiv_id":"2311.06204","repositories_listed":1,"syntology":null},{"url":"/paper/baitbuster-bangla-a-comprehensive-dataset-for","title":"BaitBuster-Bangla: A Comprehensive Dataset for Clickbait Detection in Bangla with Multi-Feature and Multi-Modal Analysis","date":"2023-10-13","arxiv_id":"2310.11465","repositories_listed":1,"syntology":null},{"url":"/paper/a-novel-contrastive-learning-method-for","title":"A Novel Contrastive Learning Method for Clickbait Detection on RoCliCo: A Romanian Clickbait Corpus of News Articles","date":"2023-10-10","arxiv_id":"2310.06540","repositories_listed":1,"syntology":null},{"url":"/paper/clickbait-detection-via-large-language-models","title":"Clickbait Detection via Large Language Models","date":"2023-06-16","arxiv_id":"2306.09597","repositories_listed":1,"syntology":null},{"url":"/paper/a-two-level-classification-approach-for","title":"A Two-Level Classification Approach for Detecting Clickbait Posts using Text-Based Features","date":"2017-10-23","arxiv_id":"1710.08528","repositories_listed":1,"syntology":null},{"url":"/paper/clickbait-detection-in-tweets-using-self","title":"Clickbait Detection in Tweets Using Self-attentive Network","date":"2017-10-15","arxiv_id":"1710.05364","repositories_listed":1,"syntology":null},{"url":"/paper/we-built-a-fake-news-click-bait-filter-what-1","title":"We Built a Fake News / Click Bait Filter: What Happened Next Will Blow Your Mind!","date":"2017-09-01","arxiv_id":null,"repositories_listed":1,"syntology":null}],"syntology_records":0,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}