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Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (10): 51-59    DOI: 10.11925/infotech.2096-3467.2021.0113
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Topic Analysis of LIS Big Data Research with Overlay Mapping
Chen Shiji,Qiu Junping(),Yu Bo
Chinese Academy of Science and Education Evaluation (CASEE), Hangzhou Dianzi University,Hangzhou 310018, China
Academy of Data Science and Informetrics (ADSI), Hangzhou Dianzi University, Hangzhou 310018, China
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Abstract  

[Objective] This paper explores the topics of big data research in Library and Information Science (LIS), aiming to reveal their developing trends. [Methods] We used “big data” as keyword to search the Web of Science and then constructed a test collection with the retrieved documents. Based on the citation analysis, we removed those irrelevant documents. Then, we used the Leiden algorithm and the VOSviewer to construct the science mapping on LIS big data research. Finally, we created the overlay mapping of research topics. [Results] According to the citation analysis, LIS big data research focuses on big data and social media analysis, followed by cloud computing, machine learning, big data technologies (such as Hadoop and MapReduce), health information, precision medicine, industry 4.0 and Internet of Things. [Limitations] We only analyzed the themes and development trends of LIS big data research from the macro-perspective. [Conclusions] Big data is an important LIS research topic. Popular studies focuses on big data and social media analysis. Machine learning, health information, precision medicine, Industry 4.0 and the Internet of Things are the important directions for Library and Information Science.

Key wordsBig Data      Knowledge Mapping      Overlay Mapping      Library and Information Science     
Received: 02 February 2021      Published: 23 November 2021
ZTFLH:  G350  
Fund:National Social Science Fund of China(19ZDA348)
Corresponding Authors: Qiu Junping,ORCID:0000-0001-8660-3491     E-mail: jpqiu@hdu.edu.cn

Cite this article:

Chen Shiji, Qiu Junping, Yu Bo. Topic Analysis of LIS Big Data Research with Overlay Mapping. Data Analysis and Knowledge Discovery, 2021, 5(10): 51-59.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2021.0113     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2021/V5/I10/51

数据来源 关键词 研究内容
Web of Science数据库 标题或关键词包含“Data Science”或“Big Data” 数据科学的最高贡献来自计算机科学研究领域,图情领域的贡献很小,但文章数量表现增长趋势[8];
从图情领域探讨数据科学的主题[9] ;
评估图情领域在大数据方面的研究成果以及南非在1992-2019年期间的贡献[10];
图书馆和信息管理领域的大数据研究趋势[11];
借助SATI 和SPSS进行关键词共现和聚类分析,揭示国际图情领域大数据研究的热点与特征[12]
LISTA和WoS数据库
(截至2016年10月)
标题或关键词
包含“Big Data”
审查图情领域包含大数据定义的文章,收集了35个定义,并对这些定义进行内容分析和统计描述[13]
中国知网(学术期刊)或维普中文期刊数据库 主题包含“大数据” 通过聚类分析、战略坐标图分析和核心-边缘结构分析等方式挖掘国内图情领域大数据研究热点[14];
图情领域近5年或10年大数据主题的研究热点[15];
近5年或10年大数据主题的研究热点[16]
Web of Science和中国知网(学术期刊) 主题包含“大数据” 利用文本数据挖掘的方法识别和比较国内外图情领域不同时期的大数据研究主题,分析研究主题的演变情况[17]
Research Hotspots on Big Data Research of Library and Information Science
Science Mapping on Big Data
Paper Overlay Mapping on Big Data of Library and Information Science
Citation Overlay Mapping on Big Data of Library and Information Science
类团代码 图情论文数 图情施引次数 关键词
C0 71 685 social media, machine learning, privacy, twitter, ethics
C1 61 881 big data analytics, social media, supply chain management, business analytics
C13 13 163 internet of things, data mining, privacy, machine learning, social network analysis
C6 12 175 MapReduce, machine learning, data mining, feature selection, classification
C2 8 169 cloud computing, MapReduce, Hadoop, security, cloud storage
C3 7 102 internet of things, cloud computing, edge computing, fog computing, smart city
C5 8 121 social media, deep learning, machine learning, human mobility, mobile phone data
C10 4 109 machine learning, data science, climate change, digital agriculture, smart farming
C4 1 102 machine learning, deep learning, artificial intelligence, electronic health records, precision medicine
C7 1 50 machine learning, deep learning, internet of things, big data analytics, security
C8 1 63 industry 4.0, internet of things, cloud computing, smart manufacturing, cloud manufacturing
The Communities Focused by Library and Information Science and Their Citations
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doi: 10.1177/0961000617742451
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[14] (Wang Chunhua, Li Wei, Wen Tingxiao. The Research Hotspot of Big Data in Library and Information Science of China[J]. Documentation,Information & Knowledge, 2015(4): 82-89.)
[15] 赵蓉英, 魏绪秋. 我国图书情报学领域大数据研究演进特征分析[J]. 情报科学, 2017, 35(5): 3-7, 14.
[15] (Zhao Rongying, Wei Xuqiu. Analysis of Evolutional Characteristics of Big Data in Library and Information Science in China[J]. Information Science, 2017, 35(5): 3-7,14.)
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[16] (Yu Qiuyu, Xu Yuequan. The Research Hotspots of Big Data in China’s Library and Information Science in Recent Five Years[J]. Research on Library Science, 2020(8): 10-18.)
[17] 陈军营, 白如江, 王效岳, 等. 中外图情领域大数据近十年(2007—2016)研究现状与发展趋势分析[J]. 情报科学, 2018, 36(7): 104-110.
[17] (Chen Junying, Bai Rujiang, Wang Xiaoyue, et al. Research Status and Development Trend Analysis of Big Data in the Field of Chinese and Foreign Library and Information Science in Recent 10 Years (2007—2016)[J]. Information Science, 2018, 36(7): 104-110.)
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doi: 10.1016/j.joi.2016.07.008
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doi: 10.1038/s41598-019-41695-z pmid: 30914743
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doi: 10.1016/j.ijinfomgt.2016.07.009
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