Deep Learning and Data Analytics Applications in Social Networks

Dear Colleagues,

Social media is a critical component of our lives, with billions of interactions from across the globe each day. This scale creates two corresponding problems. First, the related data is extremely diverse and unlabeled, with different languages and modalities (video, text, sound, etc.). Enabling training models to perform adequately across this diverse space, and across time, is an ongoing challenge. Second, deep learning and data analysis can struggle to scale to the level of billions of users. This means that benefits of social media, e.g., recommendation systems that connect similar users or tools that stop hate or misinformation from propagating, may struggle to handle user data effectively. Moreover, the misuse of deep learning tools could reveal private information about users, such as their age, gender, or sexual orientation, based on their “likes”. Alternatively, models without sufficient guardrails could leak the users’ data it was trained on. Finally, user satisfaction requires AI models to perform fairly across both large and small communities.

This Special Issue will motivate researchers to share key deep learning and scalable data analytics tools that help improve the lives of users across these diverse social media landscapes. The topics include, but are not limited to, the following:

1. Scalable network science tools, including
   1. Community detection;
   2. Multidimensional and multilayer network tools;
   3. Temporal network tools.
2. Graph foundational models and graph-based neural networks
3. Efficient searching in networks
4. Scalable deep learning
5. Multi-modal analysis
6. Fair AI applied to social media
7. Natural language processing, including supervised and semi-supervised labeling
8. Computer vision tools and CV-based image labeling
9. Scalable large language model tools
10. Tabular data models applied to social media
11. Social media-based knowledge graphs
12. Edge computing applied to social media

Dr. Keith Burghardt
Guest Editor

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