计算机科学
计算社会学
嵌入
数据科学
领域(数学)
钥匙(锁)
方案(数学)
社交网络(社会语言学)
开放式研究
情态动词
符号(正式)
社会化媒体
万维网
人工智能
数学
数学分析
化学
高分子化学
程序设计语言
纯数学
计算机安全
作者
Huimin Chen,Cheng Yang,Xuanming Zhang,Zhiyuan Liu,Maosong Sun,Jian Jin
出处
期刊:Journal of social computing
[Institute of Electrical and Electronics Engineers]
日期:2021-06-01
卷期号:2 (2): 103-156
被引量:8
标识
DOI:10.23919/jsc.2021.0011
摘要
Computational Social Science (CSS), aiming at utilizing computational methods to address social science problems, is a recent emerging and fast-developing field. The study of CSS is data-driven and significantly benefits from the availability of online user-generated contents and social networks, which contain rich text and network data for investigation. However, these large-scale and multi-modal data also present researchers with a great challenge: how to represent data effectively to mine the meanings we want in CSS? To explore the answer, we give a thorough review of data representations in CSS for both text and network. Specifically, we summarize existing representations into two schemes, namely symbol-based and embedding-based representations, and introduce a series of typical methods for each scheme. Afterwards, we present the applications of the above representations based on the investigation of more than 400 research articles from 6 top venues involved with CSS. From the statistics of these applications, we unearth the strength of each kind of representations and discover the tendency that embedding-based representations are emerging and obtaining increasing attention over the last decade. Finally, we discuss several key challenges and open issues for future directions. This survey aims to provide a deeper understanding and more advisable applications of data representations for CSS researchers.
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