TY - JOUR
T1 - 空间和地理计算与计算社会学的融合路径
AU - Yue, Yang
AU - Liu, Yu
AU - Chen, Yunsong
AU - He, Li
AU - Chen, Chen
AU - Li, Wenwen
AU - Qin, Kun
AU - Jia, Tao
AU - Xu, Gang
AU - Wang, Fahui
AU - Wang, Jingyuan
AU - Xie, Xing
AU - Xu, Fengli
AU - Xu, Yang
AU - Su, Shiliang
AU - Gui, Zhipeng
AU - You, Lan
AU - Zhang, Mingda
AU - Zhang, Feng
AU - Zhang, Xiaoxiang
AU - Zhao, Bo
AU - Zhao, Yaolong
AU - Zhou, Yulun
AU - Huang, Bo
AU - Cao, Kai
N1 - Publisher Copyright:
© 2022, Editorial Board of Geomatics and Information Science of Wuhan University. All right reserved.
PY - 2022/1/5
Y1 - 2022/1/5
N2 - 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.
AB - 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.
KW - Computational social science
KW - Geo⁃social computing
KW - Social computing
KW - Spatial computing
KW - Spatial⁃social computing
UR - https://www.scopus.com/pages/publications/85122917838
U2 - 10.13203/j.whugis20210619
DO - 10.13203/j.whugis20210619
M3 - 文章
AN - SCOPUS:85122917838
SN - 1671-8860
VL - 47
SP - 1
EP - 18
JO - Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University
JF - Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University
IS - 1
ER -