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

被引：1

作者：

Wu J. ^{[1
]}

Ye B. ^{[1
]}

Gong Q. ^{[1
]}

Oksanen A. ^{[2
]}

Li C. ^{[3
]}

Qu J. ^{[4
]}

Tian F.F. ^{[5
]}

Li X. ^{[6
]}

Chen Y. ^{[1
]}

机构：

[1] Shanghai Key Lab of Intelligent Information Processing, The School of Computer Science, Fudan University, Shanghai

[2] Tampere University, Faculty of Social Sciences, Tampere

[3] School of Information Science and Technology, Fudan University, Shanghai

[4] Shanghai Artificial Intelligence Laboratory, Shanghai

[5] School of Social Development and Public Policy, Fudan University, Shanghai

[6] Institute of Complex Networks and Intelligent Systems, Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai

来源：

Journal of Social Computing | 2022年 / 3卷 / 04期

关键词：

bibliometric; Digital Bibliography and Library Project (DBLP); evolution; social computing; visualization;

D O I：

10.23919/JSC.2022.0018

中图分类号：

学科分类号：

摘要：

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. © 2020 Tsinghua University Press.

引用

页码：287 / 302

页数：15

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