Crowd intelligence (CI) phenomena are widespread, including collective intelligence, swarm intelligence, as well as other new group phenomena with larger scale and closer interconnection between human intelligence and artificial intelligence. The International Journal of Crowd Science aims to facilitate the discovery of fundamental theories in understanding the networked society of human in the loop AI and crowd intelligence, and to explore related technologies and new ways of developing and harnessing crowd intelligence to improve the efficiency of CI network system, as well as socioeconomic outcomes.

The journal welcomes theoretical, technical and applied articles that draw on contributions from multiple fields such as system and information theory, computer science, engineering, management, economics, sociology, and psychology, etc. The title covers but is not limited to:

• Crowd Intelligence: measurement and interaction, Collective Intelligence, Group Intelligence, Edge/Cloud Intelligence, Human-in-the-loop Artificial Intelligence (HIT-AI), Quantum AI algorithm, etc.
• Crowd Intelligence network system: modeling, simulation, optimization, evolution, and robustness, etc.
• Crowd Intelligence related technologies: AI, Blockchain, Cloud Computing and Big Data, the Internet of Thing (IoT), etc.
• Crowd Intelligence application and influence in social science: Crowdsourcing, Crowdfunding, Electronic Commerce, E-government, Public affairs decision, Intelligent Transportation, Smart medical care and elderly care, Smart city, etc.