BaitBuster: A Clickbait Identification Framework

Md Main Uddin Rony, Naeemul Hassan, Mohammad Yousuf
2018 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
The use of tempting and often misleading headlines (clickbait) to allure readers has become a growing practice nowadays among the media outlets. The widespread use of clickbait risks the reader's trust in media. In this paper, we present BaitBuster, a browser extension and social bot based framework, that detects clickbaits floating on the web, provides brief explanation behind its decision, and regularly makes users aware of potential clickbaits.
doi:10.1609/aaai.v32i1.11378 fatcat:z4b6ohscwbfbtcdf33uicktvq4