Sora for Computational Social Systems: From Counterfactual Experiments to Artificiofactual Experiments With Parallel Intelligence

作     者：Qin, Rui Wang, Fei-Yue Zheng, Xiaolong Ni, Qinghua Li, Juanjuan Xue, Xiao Hu, Bin 

作者机构：Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing Peoples R China Chinese Acad Sci Inst Automat Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau Peoples R China Tianjin Univ Coll Intelligence & Comp Sch Comp Software Tianjin Peoples R China Beijing Inst Technol Sch Med Technol Beijing Peoples R China 

出 版 物：《IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS》 (IEEE Trans. Computat. Soc. Syst.)

年 卷 期：2024年第11卷第2期

页      面：1531-1550页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

摘      要：Welcome to the second issue of IEEE Transactions on Computational Social Systems (TCSS) of 2024. This issue showcases an impressive array of 104 regular papers alongside our Special Issue on Big Data and Computational Social Intelligence for Guaranteed Financial Security, highlighting cutting-edge research aimed at harnessing big data and computational techniques to fortify financial security amidst the digital finance evolution. With a focus on addressing the intricate challenges of financial big data, enhancing the efficacy of artificial intelligence, and covering critical topics from data mining to digital currencies, this issue underscores the vital role of cross-disciplinary efforts in mitigating financial security risks.