"Explainable AI and Network Science for Social Systems and Collective Intelligence"

Call for Papers-"Explainable AI and Network Science for Social Systems and Collective Intelligence"

Journal: Information Processing & Management

Publisher: Elsevier

Submission Deadline: 31 Mar 2027

Key Requirements:

• XAI + Network Science integration for social systems mandatory

• Multilayer/higher-order networks beyond pairwise analysis

• VSI: AINet article type selection CRITICAL during submission

Overview

Black-box AI limits social platform governance as LLMs + GNNs analyze multilayer networks, hypergraphs, group interactions shaping collective intelligence. Addresses information disorder + polarization through explainable methods revealing influence dynamics + consensus formation. First issue combining XAI + network science for trustworthy human-AI collective decision-making amid real-time digital communication.

Key Research Themes

Advanced Network Modeling:

• Multilayer networks + higher-order hypergraphs

• Dynamic influence/leadership identification

Explainable AI Applications:

• XAI for social behavior prediction + causal inference

• Knowledge graphs explaining collective intelligence

Human-AI Systems:

• LLM agents in online communities

• Reputation/trust formation in adversarial settings

Collective Behavior Analysis:

• Opinion dynamics + polarization modeling

• Early-warning signals + risk forecasting

Submission Instructions

1. Access EVISE Submission System
2. Register/Login (new users create EVISE account)
3. Submit to Special Issue category "VSI: AINet"
4. CRITICAL: Select "VSI: AINet" from Article Type dropdown
5. Format strictly per Author Guidelines
6. Originality: Manuscripts not under review elsewhere

Timeline: Published 01 Apr 2026 | Closes 31 Mar 2027

Guest Editor Team

• Dr. Tao Wen, Alliance Manchester Business School, University of Manchester, UK (tao.wen@manchester.ac.uk)

• Asst. Prof. Xinyi Zhou, Boise State University, USA (xinyizhou@boisestate.edu)

• Prof. Richard Allmendinger, Alliance Manchester Business School, University of Manchester, UK (richard.allmendinger@manchester.ac.uk)

• Assoc. Prof. Kang Hao Cheong, Nanyang Technological University, Singapore (kanghao.cheong@ntu.edu.sg)

Why This Issue Matters

5B social media users generate 500M tweets/day requiring explainable collective intelligence models beyond black-box predictions. Misinformation cascades + AI-mediated polarization demand trustworthy XAI frameworks for platform governance. 20% citation advantage accelerates responsible AI deployment addressing human-AI decision-making + network governance at global scale.

ServiceSetu Academics — Premier Platform for Academic Opportunities & Research Collaboration
Visit official website of the publisher