Aims and scope
Human-Centric Intelligent Systems is an international peer-reviewed journal which is dedicated to disseminating the latest research findings on all theoretical and practical applications in human-centric intelligent systems, and to providing cutting-edge theoretical and algorithmic insights in human-centric computing and analytics.
In past decades, the trajectory of human daily activities among human beings and interacted with cyberspace has led to a large amount of human-centric digital information at an unprecedented scale, both in depth and in breadth. This presents urgent challenges in studying effective methodologies, techniques and technical tools for representing, modelling, analyzing, understanding and managing human behaviors, social and cultural phenomena and dynamics both in the physical and in the cyber world. Multiple categories of information sources, digital behavior trajectories within communities and advancements in behavioral and social computing have the potential to address these challenges such as information diffusion, community dynamics, trust, privacy and security issues, and to open up a new multidisciplinary research field of human-centric intelligence to better serve humanity. Hence this journal aims to advance the promising perspectives on fundamental theories, computational models and technological solutions and systems related to the emerging areas of human-centric intelligent systems.
Human-Centric Intelligent Systems encourages research covering the current key research interests in managing the interactions between users, organizations, communities and computing systems, as well as modelling and governance of social and organizational concepts, e.g. community, trust, credibility and privacy. Topics covered include, but are not limited to, the following:
- Human-centered AI
- Human-centric data and management
- Information diffusion and modelling
- Diffusion source identification and network analysis
- Classification, ranking, summarizing and recommendation
- Social influence analysis
- Community detection and dynamics
- Disinformation and misinformation detection
- Network structure and community evolution analysis
- User modelling, personalization and recommendation
- Responsible AI, fairness and explainability
- Behavioral/choice modelling
- Behavioral dynamics and simulation
- User behavior and influence analysis
- Community/crowd behavioral analysis
- Event tracking and detection
- Trust computing and privacy preservation
- Social and ethical issue analysis
- Intelligent system design and evaluation
- Mobile, ubiquitous and pervasive sensing
- Data mining in mobile and social sensing
- Applications in healthcare, mobility, economics and society