Special Session
Special Session on
Explainable AI for Understanding Online Behaviors and Mitigating Radicalization -
XAI-OBRAD
2024
20 - 22 November, 2024 - Porto, Portugal
Within the 1st International Conference on Explainable AI for Neural and Symbolic Methods - EXPLAINS 2024
* CANCELLED *
CO-CHAIRS
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Danilo Cavaliere
University of Salerno
Italy
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Brief Bio
Danilo Cavaliere received both the master degree cum laude in computer science and the Ph.D. degree with judgement excellent from the University of Salerno (Italy) in 2014 and 2020, respectively. He works now as a researcher for the same institution and he is involved in the SEcurity and RIghts In the CyberSpace (SERICS) research project, that is funded by European Community. Dr. Cavaliere is in the editorial board of Neurocomputing journal and was in Program Committees of international conferences, such as IEEE Symposium Series on Computational Intelligence (SSCI) and World Conference on eXplainable Artificial Intelligence (xAI). His research interests include artificial and computational intelligence, knowledge-based systems, soft computing, intelligent agents, data mining and knowledge discovery, on which he has published many papers.
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Giuseppe Fenza
University of Salerno
Italy
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Brief Bio
Giuseppe Fenza (Member, IEEE) received the Graduate degree and the Ph.D. degree in computer sciences from the University of Salerno, Italy, in 2004 and 2009, respectively. He is currently an Associate Professor in computer science with the University of Salerno. He has over 60 publications in fuzzy decision making, knowledge extraction and management, situation and context awareness, semantic information retrieval, service oriented architecture, and ontology learning. More recently, he has worked in automating open source intelligence and big data analytics for counterfeiting extremism and supporting information disorder awareness. His research interests include computational intelligence methods to support semantic-enabled solutions and decision-making.
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Rajesh Sharma
University of Tartu
Estonia
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Brief Bio
Rajesh is presently (from January 2020 - present) working as Associate Professor at the Institute of Computer Science, University of Tartu (UT), Estonia. Earlier, Rajesh joined University of Tartu in August 2017 and worked as a senior researcher till December 2019. From Jan 2014 to July 2017, he has held Research Fellow and postdoc positions at the University of Bristol, Queen's University Belfast, UK and the University of Bologna, Italy. Prior to that, he completed his PhD from Nanyang Technological University, Singapore in December 2013. He has also worked in IT industry for about 2.5 years after completing his master's from Indian Institute of Technology (IIT), Roorkee, India. Rajesh leads the Computational Social Science Group (https://css.cs.ut.ee/) and has written over 80 research articles. Rajesh is associate editor for Journal of Social Network Analysis and Mining. His group works on problems related to understanding societal issues such as misinformation, hate speech, segregation, users' behavior using digital traces such as financial transactions, mobile call data records and more importantly social media data. To accomplish his research Rajesh has received funding from various Horizon2020 and CHIST-ERA projects.
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SCOPE
The rise of social media platforms has transformed information dissemination and online community formation but has also led to unwanted effects, such as echo chambers, user polarization, and radicalization pathways. In these environments, people are exposed to information that reinforces their existing beliefs, contributing to polarization and the spread of extremist ideologies.
To understand and contrast these phenomena, user behaviors should be analyzed considering various network and user features. In this regard, Explainable Artificial Intelligence (xAI) approaches can help
unfolding the mechanisms underlying such phenomena. This special session aims to explore the intersection of xAI and online behavior analysis, focusing on novel research challenges and solutions to combat disinformation, echo chambers, and related phenomena leading to polarization and radicalization. All the research teams involved in the SERICS research project (https://serics.eu/) are encouraged to submit their contribution to this special session.
HAMISON - Holistic Analysis of Organised Misinformation Activity in Social Networks
FOUNDATION SERICS (SEcurity and RIghts In the CyberSpace)
TOPICS OF INTEREST
Topics of interest include, but are not limited to:
- Exploring the Role of eXplainable AI in Understanding Online Behavior Dynamics
- Detecting and Mitigating Echo Chambers through Interpretable AI Techniques
- Leveraging xAI for quantifying the impact of Recommendation Systems on Radicalization Pathways
- Combating Disinformation and Fake News with Transparent AI Solutions
- Advancements in Explainable AI for Promoting Content Diversity and Reducing Polarization on Social Media Platforms
IMPORTANT DATES
Paper Submission:
September 20, 2024
Authors Notification:
October 4, 2024
Camera Ready and Registration:
October 14, 2024
SPECIAL SESSION PROGRAM COMMITTEE
Available soon.
PAPER SUBMISSION
Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines.
Papers must be submitted electronically via the web-based submission system using the appropriated button on this page.
PUBLICATIONS
After thorough reviewing by the special session program committee, all accepted papers will be published in a special section of the conference proceedings book - under an ISBN reference and on digital support - and submitted for indexation by SCOPUS, Google Scholar, DBLP, Semantic Scholar, EI and Web of Science / Conference Proceedings Citation Index.
SCITEPRESS is a member of CrossRef (http://www.crossref.org/) and every paper is given a DOI (Digital Object Identifier).
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library