BaitBuster: A Clickbait Identification Framework

Rony, Md Main Uddin (The University of Mississippi) | Hassan, Naeemul (The University of Mississippi) | Yousuf, Mohammad (The  University of Oklahoma )

AAAI Conferences 

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.

Duplicate Docs Excel Report

Title
None found

Similar Docs  Excel Report  more

TitleSimilaritySource
None found