%A Chen Shiji, Qiu Junping, Yu Bo %T Topic Analysis of LIS Big Data Research with Overlay Mapping %0 Journal Article %D 2021 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2021.0113 %P 51-59 %V 5 %N 10 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_5178.shtml} %8 2021-10-25 %X

[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.