Applying Machine Learning for Combating Fake News and Internet/Media Content Manipulation

in Special Issue   Posted on March 28, 2020 

Information for the Special Issue

Submission Deadline: Fri 25 Sep 2020
Journal Impact Factor : 5.472
Journal Name : Applied Soft Computing
Journal Publisher:
Website for the Special Issue:
Journal & Submission Website:

Special Issue Call for Papers:

Nowadays, societies, businesses and citizens are strongly dependent on information, and information became one of the most crucial (societal and economical) values. People expect that both traditional and online media provide trustful and reliable news and content. The right to be informed is one of fundamental requirements allowing for taking right decisions in a small scale (e.g., during shopping) and large scale (e.g., during general or presidential elections).

However, information is not always reliable, because digital content may be manipulated, and its spreading could be also used for disinformation. This is true especially with the proliferation of online media, where news travel fast and are often based on User Generated Content (UGC), while there is often little time and few resources for the information to be carefully cross-checked. Moreover, disinformation and media manipulation can be part of hybrid warfare and malicious propaganda. Such false content should be detected as soon as possible to avoid its negative influence on the readers and in some cases on political decisions.

Part of these challenges and vivid problems can be addressed by innovative machine learning, artificial intelligence and soft computing methods. Therefore, the main aim of this special issue is to gather a set of high-quality papers presenting new approaches and solutions for media and content manipulation and disinformation detection. We also encourage papers concerning the problem of early detection of radicalization and hate speech based on fake information and/or manipulated content.

The list of possible topics includes, but is not limited to:

  • machine learning and soft computing methods for media content and disinformation analysis, especially with correlation in heterogenous types of data (images, text, tweets etc.)
  • fake news detection in social media
  • application of Natural Language Processing (NLP) for the disinformation analysis
  • feature extraction algorithms for content manipulation
  • sentiment analysis methods for fake news detection
  • images and video manipulation recognition
  • discovering the real content in changed images and videos
  • early detection of radicalization/hate speech
  • architectural frameworks and design for media content manipulation and disinformation detection
  • blockchain applications for trusted media content
  • learning how to detect content manipulation in the presence of the concept drift
  • learning how to detect fake news with limited ground truth access and on the basis of limited data sets, including one-shot learning
  • machine learning and soft computing advances in IPR and copyright challenges and protection
  • human rights, legal and societal aspects of media content manipulation and disinformation detection
  • case studies and real-world applications (e.g., media sector, internet content search engines, educational sector, agri-food sector, etc.)


Start date for paper submission: 4th November 2019

Submission deadline: September 25th, 2020

First Round of Review: Maximum 2 months after submission date

Submission of Revised Paper: Maximum 1 month after 1st review notification

Final Notification: Maximum 2 months after re-submission

Special Issue closing date: 20th March 2021

Guest Editors

Prof. Michal Choras, UTP University of Science and Technology, Poland e-mail: [email protected]

Dr. Konstantinos Demestichas, National Technical University of Athens, Greece e-mail: [email protected] 

Dr. Alvaro Herrero, University of Burgos, Spain e-mail: [email protected] 

Prof. Michal Wozniak, Wroclaw University of Science and Technology, Poland. e-mail: [email protected] 

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