Conference Information

AICSS 2026: International Symposium on Artificial Intelligence and Computational Social Sciences

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Submission Date:
2026-09-04 Due in 30 days
Notification Date:
2026-09-11
Conference Date:
2026-09-18
Location:
Beijing, China
Years:
2
Viewed: 5107   Tracked: 0   Attend: 2

Call For Papers

AICSS 2026 (International Symposium on Artificial Intelligence and Computational Social Sciences) is an academic conference held in Beijing, China on 2026-09-18. The paper submission deadline is 2026-09-04. Acceptance notifications are sent on 2026-09-11.

The topics of interest for submission include, but are not limited to: Big Data And Knowledge Engineering Database And Data Warehouse Text Mining Social Network Analysis Online Behavior Analysis Sentiment Analysis Group Behavior Modeling And Simulation Urban Computing Computational Social Psychology Multimodal Interaction Social Computing Knowledge Graph Construction, Retrieval And Reasoning Social Media Mining Computational Linguistics Causal Reasoning Machine Learning ◕ Artificial Intelligence · artificial intelligence · artificial neural networks · deep learning · natural language processing · computer vision · knowledge graph construction · interpretable machine learning · embodied intelligence large language model ◕ Social Computing Science · social network analysis · social media mining · smart city · social recommendation · complex social system modeling. ◕ Language Model · the integration and development of large language model and social computing method · the interpretability of large language model · the application of large language model in social media · the risk and safety of large language model and the alignment of big language model values. ◕ Big data · big data representation · big data analysis and processing · big data structure · big data fusion · big data inheritance · big data technology · big data and artificial intelligence · big data and deep learning ◕ language Intelligence and Smart Foreign Language Education · application of artificial intelligence in personalized learning system · data analysis and optimization of online learning platform · prediction and evaluation model of learning effect · research on education equity based on network data · analysis of teachers ' behavior and intelligent teaching support
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