The Internal Journal on Social Computing and Social Intelligence (The SCSI Journal) is a peer reviewed, openaccess, interdisciplinary journal publishing original research at the interface of the computational and social sciences. The journal pursues two complementary aims — understanding society through computation, and serving people through intelligence. It addresses an international audience of researchers and practitioners in computer science, artificial intelligence, sociology, management, communication, economics, psychology, public policy, and complexity science, and particularly encourages work grounded in platforms, populations, and institutional settings underrepresented in the existing literature.

Topics of interest include, but are not limited to:

(1) Methods of computational social science 

measurement and causal inference with largescale social data; computational text and multimodal analysis; social network analysis; agentbased modeling and social simulation; online and field experiments; research data infrastructure.

(2) Social media and information ecosystems

information diffusion and opinion dynamics; polarization and group communication; misinformation detection and content governance; societal effects of recommender systems and platform mechanisms.

(3) Social intelligence and intelligent agents

socially aware artificial intelligence; agents based on large language models and generative social simulation; machine theory of mind, affective computing, and social reasoning; cooperation and norms in multiagent systems.

(4) Human–AI collaboration and collective intelligence

hybrid human–AI teams and organizations; crowdsourcing and crowd computing; collective decisionmaking and deliberation; trust and reliance calibration in human–AI interaction.

(5) Collective behavior and social complex systems

evolution of cooperation and social norms; computational studies of mobility and inequality; urban computing and spatiotemporal behavior; collective behavior in economic and financial systems; societal responses in public health and crises.

(6) Computational social governance

algorithmic and platform governance; computational policy evaluation and simulation; digital government and smart cities; social risk sensing and emergency management.

(7) Ethics and societal impact

algorithmic fairness, transparency, and accountability; privacy and data rights; assessment of the societal consequences of AI; digital divides and accessibility; AI safety in social contexts.

We invite you to join us in shaping the discourse on how data intelligence can be leveraged to understand, predict, and ultimately improve complex social computing systems.