乐阳, 刘瑜, 陈云松, 贺力, 陈晨, 李文雯, 秦昆, 贾涛, 许刚, 王法辉, 王静远, 谢幸, 徐丰力, 徐阳, 苏世亮, 桂志鹏, 游兰, 张明达, 张丰, 张晓祥, 赵博, 赵耀龙, 周钰伦, 黄波, 曹凯. 空间和地理计算与计算社会学的融合路径[J]. 武汉大学学报 ( 信息科学版), 2022, 47(1): 1-18. DOI: 10.13203/j.whugis20210619
引用本文: 乐阳, 刘瑜, 陈云松, 贺力, 陈晨, 李文雯, 秦昆, 贾涛, 许刚, 王法辉, 王静远, 谢幸, 徐丰力, 徐阳, 苏世亮, 桂志鹏, 游兰, 张明达, 张丰, 张晓祥, 赵博, 赵耀龙, 周钰伦, 黄波, 曹凯. 空间和地理计算与计算社会学的融合路径[J]. 武汉大学学报 ( 信息科学版), 2022, 47(1): 1-18. DOI: 10.13203/j.whugis20210619
YUE Yang, LIU Yu, CHEN Yunsong, HE Li, CHEN Chen, LI Wenwen, QIN Kun, JIA Tao, XU Gang, WANG Fahui, WANG Jingyuan, XIE Xing, XU Fengli, XU Yang, SU Shiliang, GUI Zhipeng, YOU Lan, ZHANG Mingda, ZHANG Feng, ZHANG Xiaoxiang, ZHAO Bo, ZHAO Yaolong, ZHOU Yulun, HUANG Bo, CAO Kai. Integration Path of Spatial and Geo-Computing and Computational Social Science[J]. Geomatics and Information Science of Wuhan University, 2022, 47(1): 1-18. DOI: 10.13203/j.whugis20210619
Citation: YUE Yang, LIU Yu, CHEN Yunsong, HE Li, CHEN Chen, LI Wenwen, QIN Kun, JIA Tao, XU Gang, WANG Fahui, WANG Jingyuan, XIE Xing, XU Fengli, XU Yang, SU Shiliang, GUI Zhipeng, YOU Lan, ZHANG Mingda, ZHANG Feng, ZHANG Xiaoxiang, ZHAO Bo, ZHAO Yaolong, ZHOU Yulun, HUANG Bo, CAO Kai. Integration Path of Spatial and Geo-Computing and Computational Social Science[J]. Geomatics and Information Science of Wuhan University, 2022, 47(1): 1-18. DOI: 10.13203/j.whugis20210619

空间和地理计算与计算社会学的融合路径

Integration Path of Spatial and Geo-Computing and Computational Social Science

  • 摘要: 空间和地理数据及空间计算是大数据和人工智能(artificial intelligence,AI)研究的一个主要组成领域,也为社会科学从本体论、方法论和认识论层面提供了一个进行定量和定性研究的重要维度。但是空间如何与计算社会科学结合仍处于探索阶段。通过邀请实证社会研究、地理信息科学、计算机科学等多个领域在计算社会学方向的代表学者,对大数据和AI时代新的研究和技术范式下空间和地理计算与社会计算相结合的重要议题或实现路径等阐述各自观点,希望能够对空间社会计算的发展提供研究思路。讨论认为,空间与地理研究和社会研究具有相同的底层原理,基于空间大数据的新范式为重启宏观社会学空间研究带来了重要机遇,而且空间大数据的可获得性使得中国学者能以更为主动的姿态和清晰的视野来审视和参与影响人类命运共同体的重大现实问题。但是在此过程中,还需进一步思考基础理论和框架,解决数据、计算和伦理等一系列问题,需要社会科学、地理信息科学和计算科学的共同合作和努力,以学科的进步促进社会的健康发展。

     

    Abstract:
      Objectives  Geospatial data and computing plays an important role in the era of big data and artificial intelligence(AI), and provides a dimension of social studies in term of ontological, methodological, and epistemologs aspects.
      Methods  This interview invited some influential scholars from the fields of sociology, geo-informatics, computing science and expressed their views on how spatial and geo-computing can be intergrated in computational social science.
      Results  Geospatial studies and social science share a very basic research objective which focuses on heterogeneity, and spatial big data provides an unprecedented paradigm for social studies. Also, challenges were raised on building a therotical framework, data availiablity, computing issues, and related concerns on ethics.
      Conclusions  To solve the challenges, it requires the closer collaboration among social science, geo-science, and computer science. We wish this discussion could inspire the related studies and provide a blueprint for both geospatial and social computing.

     

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