数据与计算发展前沿 ›› 2022, Vol. 4 ›› Issue (6): 77-91.

CSTR: 32002.14.jfdc.CN10-1649/TP.2022.06.008

doi: 10.11871/jfdc.issn.2096-742X.2022.06.008

• 技术与应用 • 上一篇    下一篇

我国人工智能与社会科学耦合发展的热点与趋势研究——基于CiteSpace的文献计量分析

刘嘉琪1,2,*(),杨斌艳1,2   

  1. 1.中国社会科学院,新闻与传播研究所,北京 100021
    2.中国社会科学院,传媒调查研究中心,北京 100021
  • 收稿日期:2022-06-23 出版日期:2022-12-20 发布日期:2022-12-20
  • 通讯作者: 刘嘉琪
  • 作者简介:刘嘉琪,中国社会科学院新闻与传播研究所,助理研究员,北京邮电大学与美国弗吉尼亚理工大学联合培养博士,中国社会科学院传媒调查研究中心,副主任,中国人工智能学会(CAAI)社会计算与社会智能专业委员会青年委员。主要研究领域为数据科学与新媒体传播、人工智能与变革管理。
    本文中负责论文撰写、修改。
    LIU Jiaqi, assistant research fellow, Institute of Journalism and Communication, Chinese Academy of Social Sciences; joint-cultivated doctor of Beijing University of Posts and Telecom-munications and Virginia Polytechnic Institute and State Un-iversity; deputy director of the Media Investigation Center, Chinese Academy of Social Sciences; youth committee of the Professional Committee of Social Computing and Social Intelli-gence, Chinese Association for artificial intelligence (CAAI). Her research focuses on data science and new media communi-cation, artificial intelligence and change management.
    In this paper, she is responsible for the paper drafting and revising.
    E-mail: liujq@cass.org.cn
  • 基金资助:
    国家社科基金青年项目“社交媒体时代重大疫情公众网络舆情卷入特征、机制及引导策略研究”(21CXW019);国家社科基金重大项目“我国青少年网络舆情的大数据预警体系与引导机制研究”(20&ZD013)

Research on the Hot Spots and Trends of the Coupling Development of Artificial Intelligence and Social Science in China——A Bibliometric Analysis Based on CiteSpace

LIU Jiaqi1,2,*(),YANG Binyan1,2   

  1. 1. Institute of Journalism and Communication, Chinese Academy of social sciences, Beijing 100021, China
    2. Media Investigation Center, Chinese Academy of Social Sciences, Beijing 100021, China
  • Received:2022-06-23 Online:2022-12-20 Published:2022-12-20
  • Contact: LIU Jiaqi

摘要:

【目的】人工智能的发展正在为社会科学研究带来结构性冲击与革命性机遇,厘清人工智能与社会科学跨学科融合发展的关键特征与规律,具有一定的理论及现实意义。【方法】本文利用科学计量工具CiteSpace,对中文CNKI数据库中1992—2021年我国“人工智能+社会科学”领域的相关文献进行发展态势、演变历程、前沿热点等方面的分析。【结果】我国“人工智能+社会科学”研究整体呈现“局部起伏波动,总量持续增长”趋势。研究层次呈现强技术驱动性,跨学科形成“两强多面”格局。小规模学术圈层逐渐形成,复合型高产学者仍很稀缺。研究前沿正逐渐由以“机器人”、“计算机视觉”、“知识工程”等为主的热点词汇,过渡到“智能时代”、“算法治理”、“数字经济”等主题中。【结论】人工智能为社会科学研究带来了研究范式转换与范围变化的同时,也强化了人类多视角、全方位、全领域的观察能力,提升了社会科学的解释与预测精度。本文结论有助于为社会各界合力推动人工智能社会科学学科化发展提供有益参考。

关键词: 人工智能, 社会科学, 学科化发展, 可视化文献计量

Abstract:

[Objective] The development of artificial intelligence is bringing structural impact and revolutionary opportunities to social science research. It has certain theoretical and practical significance to clarify the key characteristics and laws of the development of interdisciplinary integration. [Methods] Based on the Chinese CNKI database, this paper uses the CiteSpace scientometric tool to display the overall characteristics of the research literature on “artificial intelligence + social sciences” from 1992 to 2022 by visually analyzing their developing trend, evolution process, and frontier hotspots. [Results] According to the current domestic research status of “artificial intelligence + social sciences”, the overall trend is waves and fluctuations in part while continuous growth in total. The research level is strongly driven by technology, and interdisciplinary research forms a “two-strong and multi-faceted” pattern. Small-scale academic circles are gradually formed, but compound high-yield scholars are still scarce. The research frontier is gradually transforming from hot topics such as robotics, computer vision, and knowledge engineering to topics like intelligent age, algorithmic governance, and digital economy. [Conclusions] The development of artificial intelligence not only leads to paradigm shifts and changes in the scope of social sciences research, but also strengthens human being’s observation ability of multi-perspectives, omni-directions, and all-fields, to improve the interpretation and prediction accuracy of social sciences. Moreover, this article attempts to provide a useful reference for all sectors of society to jointly promote the disciplinary development of artificial intelligence and social sciences.

Key words: artificial intelligence, social sciences, discipline development, visual bibliometrics