Fake News Detection with Hybrid CNN-LSTM

Kian Long Tan, Chin Poo Lee, Kian Ming Lim

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

In the past decades, information and communication technology has developed rapidly. Therefore, social media has become the main platform for people to share and spread information to others. Although social media has brought a lot of convenience to people, fake news also spread more rapidly than before. This situation has brought a destructive impact to people. In view of this, we propose a hybrid model of Convolutional Neural Network and Long Short-Term Memory for fake news detection. The Convolutional Neural Network model plays the role of extracting representative high-level sequence features whereas the Long Short-Term Memory model encodes the long-term dependencies of the sequence features. Two regularization techniques are applied to reduce the model complexity and to mitigate the overfitting problem. The empirical results demonstrate that the proposed Convolutional Neural Network-Long Short-Term Memory model yields the highest F1-score on four fake news datasets.

Original languageEnglish
Title of host publication2021 9th International Conference on Information and Communication Technology, ICoICT 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages606-610
Number of pages5
ISBN (Electronic)9781665404471
DOIs
Publication statusPublished - 3 Aug 2021
Externally publishedYes
Event9th International Conference on Information and Communication Technology, ICoICT 2021 - Virtual, Yogyakarta, Indonesia
Duration: 3 Aug 20215 Aug 2021

Publication series

Name2021 9th International Conference on Information and Communication Technology, ICoICT 2021

Conference

Conference9th International Conference on Information and Communication Technology, ICoICT 2021
Country/TerritoryIndonesia
CityVirtual, Yogyakarta
Period3/08/215/08/21

Keywords

  • CNN
  • Fake news
  • fake news detection
  • LSTM
  • machine learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems

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