计算机科学

计算机科学 ›› 2022, Vol. 49 ›› Issue (4): 3-8.doi: 10.11896/jsjkx.yg20220402

• 基于社会计算的多学科交叉融合专题* • 上一篇    下一篇

在跨学科交叉融合中深发展社会计算与社会智能

孟小峰, 余艳   

  1. 中国人民大学信息学院 北京 100872
  • 收稿日期:2022-02-16 修回日期:2022-03-12 发布日期:2022-04-01
  • 通讯作者: 余艳 (yanyu@ruc.edu.cn)
  • 作者简介:(xfmeng@ruc.edu.cn)
  • 基金资助:
    国家自然科学基金(72172155,91846204)

Develop Social Computing and Social Intelligence Through Cross-disciplinary Fusion

MENG Xiao-feng, YU Yan   

  1. School of Information, Renmin University of China, Beijing 100872, China
  • Received:2022-02-16 Revised:2022-03-12 Published:2022-04-01
  • About author:MENG Xiao-feng,born in 1964,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include data intelligence,data governance,social computing and social intelligence.YU Yan,born in 1980,Ph.D,associate professor.Her main research interests include knowledge management,digital innovation and societal intelligence.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China(72172155,91846204).

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摘要： 数智化的时代背景为社会计算与社会智能的发展创造了新机遇,跨学科交叉融合将是其深化发展的必然之路。文中阐述了社会计算的内涵与外延,探讨了社会计算的范式转移、社会计算与社会智能的发展,由此对数智化时代的社会计算与社会智能进行了展望,提出了构建基于新型基础建设的社会智能体系的三大支柱,包括构建大规模高时变的数据智能、融合多尺度伸缩的空间智能、形成复杂适应性的社会智能。数据智能、空间智能和社会智能呈现出层次递进关系,要求数据、计算和社会的三者交织,这也要求计算科学、数据科学、空间科学、复杂科学、社会科学等多学科多领域在理论与方法上交叉融合。随着数智化技术的快速更新及其在社会经济系统中的不断渗透,社会计算与社会智能必然会在跨学科交叉融合中寻找突破与深发展。

关键词: 跨学科融合, 社会计算, 社会智能, 数据智能

Abstract: The era of digital intelligence offers new opportunities for the development of social computing and social intelligence.Cross-disciplinary fusion shall be a critical approach for its deep development.This paper elaborates the connotation and denotation of social computing, discusses the paradigm shift of social computing research, and the general development of social computing and social intelligence.Next, it looks forward to the social computing and social intelligence in the era of digital intelligence, and proposes three pillars for constructinga social intelligence system based on the new infrastructure.The construction of such an intelligent system is mainly composed by three components, including the construction of large-scale high-velocity data intelligence, the integration of multi-scale flexible spatial intelligence, and the formation of complex adaptive social intelligence.There is a level progression from data intelligence to social intelligence, in which data, computing and society are entangled.As such, computing science, data science, spatial science, complex science and social science are requested to interact from both theoretical and methodological perspectives.With the rapid update of digital-intelligent technologies and their penetration into the whole social-economic system, social computing and social intelligence is bound to seek breakthrough and deep development in the interdisciplinary cross-integration.

Key words: Cross-disciplinary fusion, Data intelligence, Social computing, Social intelligence

中图分类号: 

  • N05
[1] FAN R G.The Big Data/Social Computing Methodological Re-volution in Public Management Studies[J].Social Sciences in China,2018(9):74-91,205.
[2] WANG G Y,QU Z,ZHAO X L.Practical Exploration of Discipline Construction of Artificial Intelligence+[J].Computer Science,2020,47(4):1-5.
[3] MENG X F,LI Y,ZHU J H.Social Computing in the Era of Big Data:Opportunities and Challenges[J].Journal of Computer Research and Development,2013,50(12):2483-2491.
[4] BUSH V.As We May Think[J].The Atlantic Monthly,1945,176:101-108.
[5] SCHULER D.Social Computing[J].Communications of theACM,1994,37(1):28-29.
[6] WANG F Y.Artificial Societies,Computational Experiments,andParallel Systems:A Discussion on Computational Theory of Complex Social-Economic Systems[J].Complex System and Complexity Science,2004,1(4):25-35.
[7] WANG F Y,LI X C,MAO W J,et al.Basic methods and applications of social computing [M].Hangzhou:Zhejiang University Press,2013.
[8] LAZER D,PENTLAND A,ADAMIC L,et al.ComputationalSocial Science[J].Science,2009,323(5919):721-723.
[9] CONTE R,GILBERT N,BONELLI G,et al.Manifesto of Computational Social Science[J].The European Physical Journal Special Topics,2012,214(1):325-346.
[10] MENG X F.Computational Social Science and the Burgeoning Artificial Intelligence[J].People’s Forum·Academic Frontier,2019(20):32-39.
[11] WANG G C.Computational Social Science:Development Status and Prospect[N].China Social Science Journal,2020-08-18(4).
[12] BUYALSKAYAA,GALLO M,CAMERER C F.The goldenage of social science[J].Proceedings of the National Academy of Sciences,2021,118(5):1-11.
[13] LAZER D,PENTLAND A,WATTS D,et al.ComputationalSocial Science:Obstacles and opportunities[J].Science,2020,369(6507):721-723.
[14] YU Y,IBARRA J,KUMAR K,et al.Coevolution of Cyber-infrastructure Development and Scientific Progress[J].Technovation,2021,100(102180):1-16.
[15] MENG X F,WANG L X,LIU J X.Data privacy,monopoly and fairness for AI[J].Big Data Research,2020,6(1):35-46.
[16] DAI R W,LI Y D,LI Q D.Social Intelligence and Metasynthetic System[M].Beijing:Posts & Telecom Press,2013.
[17] SUN W P.Intelligent Society:The Foundation and Condition of the Construction of Communist Society[J].Studies on Mar-xism,2021(1):48-56.
[18] MENG X F,MA C H,YANG C.Survey on Machine Learning for Database Systems[J].Journal of Computer Research and Development,2019,56(9):1803-1820.
[19] CHEN G Q,WU G,GU Y D,et al.The challenges for big data driven research and applications in the context of managerial decision-making:Paradigm shift and research directions[J].Journal of Management Sciences in China,2018,21(7):1-10.
[20] LE Y,LIU Y,CHEN Y S,et al.Integration Path of Spatial and Geo-Computing and Computational Social Science[J].Geomatics and Information Science of Wuhan University,2022,47(1):1-18.
[21] TORRENS P M.Geography and computational social science[J].GeoJournal,2010,75(2):133-148.
[22] SONG X,GAO Y J,LI Y,et al.Spatial Data Intelligence:Concept,Technology and Challenges[J].Journal of Computer Research and Development,2022,59(2):255-263.
[23] CHEN G Q,ZENG D J,WEI Q,et al.Transitions of Decision-Making Paradigms and Enabled Innovations in the Context of Big Data[J].Management World,2020,36(2):95-105.
[24] SONG X F,YANG L X,CAO Q R.The Research Progress of Complexity Science[M].Beijing:Science Press,2004.
[25] ANDERSONP W.More is Different:Broken Symmetry and the Nature of the Hierarchical Structure of Science[J].Science,1972,177(4047):393-396.
[26] ZHANG J H,CHEN Z F,REN Z G,et al.A Review on Complexity Science and its Application to Economics:Based on Supported Projects and Related Research[J].Journal of Management Sciences in China,2020,23(11):117-126.
[27] WANG S Y,HU Y,XIONG X,et al.Complex Systems Management:Theory and Methods[J].Journal of Management Sciences in China,2021,24(8):1-9.
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