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Journal of Social Computing 2022, 3(4): 287-302 https://doi.org/10.23919/JSC.2022.0018
Open Access | Issue | Published: 31 December 2022

Characterizing and Understanding Development of Social Computing Through DBLP: A Data-Driven Analysis

Show Author's Information Jiaqi Wu1,  Bodian Ye1,  Qingyuan Gong1,  Atte Oksanen2,  Cong Li3,  Jingjing Qu4,  Felicia F. Tian5,  Xiang Li6,  Yang Chen1( )
Shanghai Key Lab of Intelligent Information Processing, the School of Computer Science, Fudan University, Shanghai 200438, China
Faculty of Social Sciences, Tampere University, Tampere 33100, Finland
School of Information Science and Technology, Fudan University, Shanghai 200438, China
Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
School of Social Development and Public Policy, Fudan University, Shanghai 200433, China
Institute of Complex Networks and Intelligent Systems, Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 200092, China
Keywords:
evolution, visualization, social computing, Digital Bibliography and Library Project (DBLP), bibliometric
Cite this article:
Wu J, Ye B, Gong Q, et al. Characterizing and Understanding Development of Social Computing Through DBLP: A Data-Driven Analysis. Journal of Social Computing, 2022, 3(4): 287-302. https://doi.org/10.23919/JSC.2022.0018
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Abstract Full text About this article

During the past decades, the term “social computing” has become a promising interdisciplinary area in the intersection of computer science and social science. In this work, we conduct a data-driven study to understand the development of social computing using the data collected from Digital Bibliography and Library Project (DBLP), a representative computer science bibliography website. We have observed a series of trends in the development of social computing, including the evolution of the number of publications, popular keywords, top venues, international collaborations, and research topics. Our findings will be helpful for researchers and practitioners working in relevant fields.


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About this article

Characterizing and Understanding Development of Social Computing Through DBLP: A Data-Driven Analysis

Show Author's information Jiaqi Wu1, Bodian Ye1, Qingyuan Gong1, Atte Oksanen2, Cong Li3, Jingjing Qu4, Felicia F. Tian5, Xiang Li6, Yang Chen1( )
Shanghai Key Lab of Intelligent Information Processing, the School of Computer Science, Fudan University, Shanghai 200438, China
Faculty of Social Sciences, Tampere University, Tampere 33100, Finland
School of Information Science and Technology, Fudan University, Shanghai 200438, China
Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
School of Social Development and Public Policy, Fudan University, Shanghai 200433, China
Institute of Complex Networks and Intelligent Systems, Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 200092, China

Abstract

During the past decades, the term “social computing” has become a promising interdisciplinary area in the intersection of computer science and social science. In this work, we conduct a data-driven study to understand the development of social computing using the data collected from Digital Bibliography and Library Project (DBLP), a representative computer science bibliography website. We have observed a series of trends in the development of social computing, including the evolution of the number of publications, popular keywords, top venues, international collaborations, and research topics. Our findings will be helpful for researchers and practitioners working in relevant fields.

Keywords: evolution, visualization, social computing, Digital Bibliography and Library Project (DBLP), bibliometric

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Received: 27 October 2022
Revised: 05 January 2023
Accepted: 12 January 2023
Published: 31 December 2022
Issue date: December 2022

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