Deep Learning Approach for Social Network Analysis
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 1129
Special Issue Editors
Interests: multimedia database; video and image analysis; recommender systems; knowledge management; big data; social network analysis
Special Issues, Collections and Topics in MDPI journals
Interests: social network analysis and modelling; designing of artificial intelligence models; deception activities
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the last decade, the spread of Online Social Networks (OSNs) enabled users to share different types of multimedia content through an interactive platform (i.e., text, audio, video and image).
For this reason, Social Network Analysis (SNA) has gained popularity as a way to unveil and identify useful social patterns for supporting different types of analytics (i.e., community detection, expert finding and social recommendation).
However, the continuous, exponential growth of these networks (both in terms of number of users, and in terms of the variety of different interactions that these networks allow) has made the development of efficient and effective SNA techniques a challenging computational task.
As a consequence, this new availability of data has allowed researchers to investigate the suitability of deep learning approaches to the development of intelligent innovations in Social Network Analysis. In particular, these methodologies aim to support common applications, as well as include social dynamic analysis, user behavior prediction, multimedia content and social graph evolution modeling, or social applications and services like such as information retrieval, recommendation, summarization, viral marketing, event recognition, expert finding, community detection, user profiling, security and social data privacy.
The aim of this Special Issue is to collect the most recent innovations in the design of Deep Learning models for supporting different analytics on the Online Social Networks (i.e., community detection, expert finding and influence analysis). We would like to gather researchers from different disciplines and methodological backgrounds to discuss new ideas, research questions, recent results, and future challenges in this emerging area of research and public interest. Potential topics include, but are not limited to:
- Deep Learning models for opinion mining;
- Deep Learning models for information mining;
- Deep Learning models for social recommendation;
- Deep Learning models for influence analysis;
- Deep Learning models for community detection;
- Deep Learning models for expert finding;
- Deep Learning models for event detection;
- Deep Learning models for user behavior analysis;
Deep Learning models for fake news detection and countermeasures.
Prof. Dr. Vincenzo Moscato
Dr. Giancarlo Sperlì
Dr. Antonino Ferraro
Guest Editors
Manuscript Submission Information
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Keywords
- social network analysis
- community detection
- influence analysis
- social recommendation
- expert finding
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