Machine Learning Techniques for Online Social Networks

Dear Colleagues,

This Special Issue invites original work that enriches the intersection of machine learning and online social networks (OSNs). The spectacular scale, dynamism, and multimodality of today’s OSNs—from short-video platforms to professional graphs—demand new learning paradigms that can cope with non-stationary, privacy-regulated and adversarial environments while still delivering socially-aware decisions. We solicit contributions that advance theory, algorithms and reproducible systems for representation learning, graph neural networks, federated and privacy-preserving ML, causal inference, fairness auditing, misinformation detection, recommender systems, and conversational agents within OSNs. Submissions should emphasize open data, ethical considerations, and real-world deployment experiences. Both methodological innovations and high-impact applications are welcome; reproducibility artifacts and open-source code will be strongly encouraged in the review process.

Topics of interest include but are not limited to the following:

• Rumor Blocking;
• Privacy-Preserving Learning;
• Misinformation Detection;
• Temporal Network Modeling;
• Influence Maximization Analysis;
• Multimodal Social Content Analysis;
• Community Detection and Evolution;
• Explainable and Causal Inference in OSNs;
• Recommender Systems for Social Platforms;
• Adversarial and Robust ML in Social Networks.

Dr. Yuliang Ma
Dr. Shudong Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.