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Arora, Bhavna. Content-based fake news detection using deep learning techniques : analysis, challenges and possible solutions. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2022.
Content-based fake news detection using deep learning techniques : analysis, challenges and possible solutions
Name: Hangloo, Sakshini
Organization :
Central University of Jammu. Department of Computer Science and Information Technology
Email :
sakshini.hangloo@gmail.com
Name: Arora, Bhavna
Organization :
Central University of Jammu. Department of Computer Science and Information Technology
Email :
bhavna.csit@cujammu.ac.in
keyword:
Image tempering
LCSH:
Deepfake
Abstract:
Since the past decade, social media platforms are
used widely for sharing information which may or may not be
credible. Due to this many incidents have occurred that show
how false news can have detrimental effect on the people and
hence it becomes imperative to check the credibility of online
news articles. Platforms like Facebook and Twitter have also
taken multiple initiatives in past years to check the spread of
misleading content on their platforms. Researchers have been
continuously working on providing solutions to tackle the issue
of fake news and its implications. This paper focuses on the
Content-Based Fake News Detection (FND) which deploys textbased
and visual-based approaches. In the past few years, a
more sophisticated approach i.e the Multimodal approach is
being used that combines the features of textual and visual data.
This paper highlights various techniques for content-based FND
using Deep Learning (DL) approach. These deep learning
models and frameworks have been analyzed in detail and the
results depict that there is a considerable improvement in the
overall performance when the multimodal methods are used.
Also, various techniques that might help for improving the
efficiency of the FND frameworks are also included as future
directions. This paper also presents numerous challenges that a
researcher may encounter while modelling a FND framework
and provides probable solution that might be applicable to
overcome these challenges.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2022
Modified:
2024-11-12
Issued:
2024-11-12
บทความ/Article
application/pdf
BibliograpyCitation :
In IEEE Computer Society. 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT 2022) (pp.411-417). Los Alamitos, CA : IEEE Computer Society
eng
©copyrights King Mongkut's University of Technology North Bangkok
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0.027307 วินาที
Hangloo, Sakshini
| Title | Contributor | Type |
|---|---|---|
| Content-based fake news detection using deep learning techniques : analysis, challenges and possible solutions
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Hangloo, Sakshini;Arora, Bhavna | บทความ/Article |
Arora, Bhavna
| Title | Contributor | Type |
|---|---|---|
| Analysis of various machine learning techniques used for automatic text summarization
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Jan, Abrooue;Arora, Bhavna | บทความ/Article | |
| Content-based fake news detection using deep learning techniques : analysis, challenges and possible solutions
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Hangloo, Sakshini;Arora, Bhavna | บทความ/Article |