CALL FOR PAPERS

15th International Workshop on Semantic Computing and AI for Social Networks and Organizational Knowledge SCSN-AI 2027

From User Information to Collective Intelligence in the Age of AI Agents

In conjunction with the 21st IEEE International Conference on Semantic Computing (ICSC 2027)

February 1–3, 2027 | Laguna Hills, California, USA | Hybrid (remote/in person)

Workshop website:
http://pa.icar.cnr.it/scsn27/

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SCOPE

Social and organizational networks are rapidly evolving into hybrid human–AI ecosystems, where people and intelligent agents create, exchange, recommend, interpret, and reason over information and knowledge.

Large language models, generative and agentic AI, multimodal foundation models, and knowledge-enhanced AI are changing how people communicate, collaborate, form communities, share knowledge, and make decisions. AI agents are increasingly becoming active participants in online communities, collaborative environments, and knowledge-intensive organizations.

This transition raises fundamental questions for Semantic Computing:
• How can we represent, understand, simulate, and govern social and organizational systems populated by both humans and AI agents?
• How can semantic technologies, knowledge graphs, and reasoning make generative and agentic AI more grounded, explainable, adaptive, and trustworthy?
• How can generative agents and synthetic populations be used to model social and organizational behavior reliably?
• How will AI-mediated interaction transform collective intelligence, organizational knowledge, social behavior, and human decision-making?

SCSN-AI 2027 brings together researchers and practitioners from Semantic Computing, Artificial Intelligence, Social Computing, Computational Social Science, Multi-Agent Systems, Network Science, Natural Language Processing, Human–Computer Interaction, and Organizational Science.

We particularly welcome forward-looking, interdisciplinary, and early-stage contributions addressing AI agents, human–AI societies, generative social simulation, semantic and knowledge-enhanced AI, multimodal social intelligence, and trustworthy AI-mediated systems.

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TOPICS OF INTEREST

Topics include, but are not limited to:

Agentic AI and Human–AI Social Systems
• LLM agents, generative agents, and multi-agent systems
• LLM-based social and organizational simulation
• Synthetic populations and generative digital societies
• Human–AI and agent–agent interaction
• Hybrid human–AI communities and social networks
• Agent identity, personas, memory, and long-term interaction
• Social norms, cooperation, trust, negotiation, and emergent agent behavior
• Agent coordination and collective behavior
• AI agents for collective intelligence and decision support
• Human–AI teams and collaborative intelligence
• Evaluation, behavioral fidelity, and validation of generative social simulations

Semantic Computing and Knowledge-Enhanced AI
• Knowledge graphs and semantic modeling of social and organizational networks
• LLMs, AI agents, and knowledge graphs
• GraphRAG, agentic RAG, and knowledge-enhanced retrieval
• Knowledge-enhanced generation and semantic grounding
• Semantic memory and knowledge architectures for AI agents
• Neuro-symbolic and semantic reasoning
• Organizational knowledge representation, discovery, and reasoning
• Semantic extraction from heterogeneous social data

Social Media, Communication, and Network Intelligence
• AI-driven social media and social network analytics
• AI-mediated communication and social interaction
• User, group, and community modeling
• Information diffusion, social influence, and information cascades
• Multimodal analysis of text, images, audio, and video
• Opinion, stance, emotion, and sentiment analysis
• Generative and conversational recommender systems
• Decentralized and federated social networks
• Causal inference, counterfactual analysis, and intervention modeling in social systems

Trustworthy AI and Information Integrity
• Misinformation and disinformation
• Synthetic media, deepfakes, and AI-generated content
• Content authenticity, provenance, and verification
• Explainability and interpretability
• Privacy-preserving social analytics
• Fairness, bias, accountability, and AI governance
• Trust, safety, oversight, and accountability of autonomous AI agents
• Security and robustness of AI-mediated social systems
• Manipulation, persuasion, and responsible AI-mediated interaction

Organizational and Collective Intelligence
• AI-supported knowledge sharing and organizational learning
• AI agents, AI coworkers, and human–AI teams in organizations
• Organizational networks, innovation, and social capital
• Human–AI collaborative decision-making
• Collective intelligence and group decision processes
• Social and organizational digital twins
• Generative models of organizational behavior
• AI-mediated organizations and socio-technical systems

Applications, Benchmarks, and Research Resources
• AI-mediated online communities
• Social intelligence for smart cities and urban systems
• Social behavior in mobility, energy, and infrastructure systems
• Benchmarks, datasets, and evaluation methodologies
• Reproducibility and validation of AI-based social research
• Behavioral and ecological validity of AI-based social simulations
• Novel applications combining Semantic Computing, AI agents, and social intelligence

Interdisciplinary, application-oriented, and early-stage innovative work is particularly encouraged.

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WHY SCSN-AI?

Now in its 15th edition, SCSN-AI provides a focused forum for discussing emerging ideas at the intersection of semantic technologies, artificial intelligence, social networks, and organizational knowledge.

The 2027 edition focuses on a major transition already reshaping these fields: social and organizational systems are no longer composed only of human users. AI agents are becoming participants, collaborators, information producers, decision-support actors, and increasingly autonomous components of digital communities and organizations.

SCSN-AI 2027 aims to provide a forum for research on both the opportunities and the unresolved challenges created by this transition.

We welcome:
• mature research results;
• novel methods and architectures;
• emerging and unconventional ideas;
• new datasets, benchmarks, and evaluation methodologies;
• empirical and simulation-based studies;
• interdisciplinary and application-oriented contributions.

Work that opens new research directions or critically examines the assumptions, limitations, and societal implications of AI-mediated social and organizational systems is especially welcome.

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IMPORTANT DATES

Abstract Submission: November 16, 2026
Paper Submission: November 23, 2026
Camera-Ready & Registration: December 31, 2026

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SUBMISSION

Authors are invited to submit original papers written in English and formatted according to the ICSC 2027 submission guidelines.

Workshop papers may be up to 6 pages, including figures, tables, and references, according to the current ICSC 2027 submission guidelines.

Submissions must contain original, unpublished work and must not be simultaneously submitted to another conference or journal.

Papers must be submitted electronically in PDF format through EasyChair:
https://easychair.org/conferences/?conf=scsn27

Authors are encouraged to submit an abstract by the abstract deadline and may update their submission with the complete paper by the full-paper deadline.

Each submission will undergo peer review. Accepted papers will be published in the workshop section of the IEEE ICSC 2027 conference proceedings.

At least one author of each accepted paper must register and present the paper.

Presentations may be given in person or virtually, according to the ICSC 2027 hybrid conference format.

Conference and formatting information:
http://www.ieee-icsc.org/

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ORGANIZING COMMITTEE
Shady Khalil, University of Hertfordshire, UK
Jianquan Liu, NEC, Japan
Giovanni Pilato, Italian National Research Council, Italy

CONTACT
For questions regarding SCSN-AI 2027:
scsn-ws (at) pa.icar.cnr.it
Workshop:
http://pa.icar.cnr.it/scsn27/
ICSC 2027:
http://www.ieee-icsc.org/