Abstract
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.
Cite
CITATION STYLE
Uddin Rony, M. M., Hassan, N., & Yousuf, M. (2018). BaitBuster: A clickbait identification framework. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 8216–8217). AAAI press. https://doi.org/10.1609/aaai.v32i1.11378
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