The increasing prevalence of social platforms across the web and internet has led to a data-rich, complex environment with urgent demands for efficient, scalable, and responsible computing. In this context, social networking intelligence has emerged as a vital research domain — particularly in the convergence of machine learning (ML) and natural language processing (NLP) — offering tools to mine behaviour, model cognition, and enable contextual awareness across dynamic, user-centric systems.

As the digital landscape evolves, it becomes equally important to integrate sustainability as a core principle of design and deployment. From reducing computational overhead to enhancing energy efficiency, sustainable AI emphasises minimising the environmental and social costs of intelligent systems while maximising their inclusiveness, interpretability, and fairness.

This special issue seeks innovative contributions that explore the intersection of ML, NLP, and social computing — particularly when applied to build scalable, adaptive, and ethically aware Web services. Submissions that address resource efficiency, privacy-preserving models, and socially impactful applications are particularly encouraged. We welcome research that combines cognitive modelling and user behaviour analytics with green AI initiatives, supporting the practical deployment of responsible, intelligent services in web and grid environments.

Subject Coverage
Suitable topics include, but are not limited, to the following:

Machine learning for social web and grid service intelligence
NLP-driven sentiment and intent detection on social platforms
Sustainable AI: computation models for social systems
Federated and privacy-preserving learning for user-centric services
Cognitive behaviour modelling and contextual adaptation in social media
Energy-aware and scalable NLP models for social content moderation
Social big data mining with environmental or ethical constraints
Graph neural networks for responsible social influence analysis
Human-in-the-loop and explainable AI in social service recommendation
Multimodal analysis for misinformation detection and trust modelling
Cloud-edge integration for energy-efficient social analytics
Social computing for ESG (Environmental, Social, Governance) alignment
AI for civic participation, education, and public health over networks

Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).

All papers are refereed through a peer review process.

All papers must be submitted online. To submit a paper, please read our Submitting articles page.

This is an Open Access Special Issue. There is an article processing charge of US$1600 per paper to publish in this Special Issue for authors. You can find more information on Open Access here.


Important Dates
Manuscripts due by: 28 February, 2026

Notification to authors: 30 April, 2026

Final versions due by: 31 July, 2026