Detection of Clickbait Content Spreaders on Online Social Networks-Reference-Cited by-同舟云学术

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Detection of Clickbait Content Spreaders on Online Social Networks

Published:2022-03 Issue: Volume: Page:
ISSN:
Container-title:2022 5th International Conference on Information and Computer Technologies (ICICT)
language:
Short-container-title:

Author:

Ghosh Smita¹,Das Pramita²,Ghosh Sneha³,Sen Diptaraj³

Affiliation:

1. Santa Clara University,Department of Mathematics and Computer Science (MCS),California,USA

2. National Institute of Technology,Department of Electronics and Communication Engineering,Durgapur,India

3. University of Engineering and Management,Department of CSE,Kolkata,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9844746/9844991/09845010.pdf?arnumber=9845010

Reference23 articles.

1. Too good to be true, too good not to share: the social utility of fake news

2. Sharing of fake news on social media: Application of the honeycomb framework and the third-person effect hypothesis

3. Clickbait detection using deep learning

4. Clickbait detection using word embeddings;indurthi;ArXiv Preprint,2017

5. A deep learning framework for clickbait detection on social area network using natural language cues

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