Natural Language Processing and Data Science Methods to Mitigate Digital Threats
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 April 2025 | Viewed by 461
Special Issue Editor
2. Vista Lab, ALGORITMI Centre, University of Évora, 7000-671 Évora, Portugal
Interests: artificial intelligence (question-answering, opinion mining, and persuasion detection in digital content); distributed systems; data security
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In an era where social media has become ingrained in the daily lives of people of all ages and is used to influence public opinion, artificial intelligence plays a crucial role in detecting fake news and digital threats. The proliferation of fake profiles, cyberbullying, manipulative tactics, and other harmful online behaviors has prompted significant attention from researchers. As a result, the scientific community is actively developing methods to detect false information, report harassment and scams, and enhance user safety.
This field encompasses a wide range of tasks, from data security to complex behavioral analysis, social engineering prevention, or content classification. This Special Issue aims to highlight recent advancements in addressing digital threats, leveraging cutting-edge techniques from natural language processing and data science, or other AI-based methods employed on textual and mixed online content.
Relevant topics covered in this Special Issue include, but are not limited to, the following:
- Hate speech and fake news detection;
- Online harassment, trolling, and cyberbullying detection;
- Bait link and other scams detection;
- Fake social media profile detection.
Dr. José Saias
Guest Editor
Manuscript Submission Information
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Keywords
- natural language processing
- cybersecurity
- misinformation
- deep learning
- threat modeling
- large language models
- identity theft
- text forensics
- fact-checking
- data science
- text classification
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