scholarly journals Research Status and Trends of Science and Technology Evaluation in China—Visual Analysis Based on Knowledge Mapping

2020 ◽  
Vol 12 (06) ◽  
pp. 199-210
Author(s):  
Honggang Yang ◽  
Haijing Zhang
2016 ◽  
Vol 31 (4) ◽  
pp. 380-385
Author(s):  
王东平 WANG Dong-ping ◽  
谢应涛 XIE Ying-tao ◽  
欧阳世宏 OUYANG Shi-hong ◽  
朱大龙 ZHU Da-long ◽  
许鑫 XU Xin ◽  
...  

2020 ◽  
Vol 9 (11) ◽  
pp. 632
Author(s):  
Ziyi Wang ◽  
Debin Ma ◽  
Ru Pang ◽  
Fan Xie ◽  
Jingxiang Zhang ◽  
...  

Social Media Big Data (SMBD) is widely used to serve the economic and social development of human beings. However, as a young research and practice field, the understanding of SMBD in academia is not enough and needs to be supplemented. This paper took Web of Science (WoS) core collection as the data source, and used traditional statistical methods and CiteSpace software to carry out the scientometrics analysis of SMBD, which showed the research status, hotspots and trends in this field. The results showed that: (1) More and more attention has been paid to SMBD research in academia, and the number of journals published has been increased in recent years, mainly in subjects such as Computer Science Engineering and Telecommunications. The results were published primarily in IEEE Access Sustainability and Future Generation Computer Systems the International Journal of eScience and so on; (2) In terms of contributions, China, the United States, the United Kingdom and other countries (regions) have published the most papers in SMBD, high-yield institutions also mainly from these countries (regions). There were already some excellent teams in the field, such as the Wanggen Wan team at Shanghai University and Haoran Xie team from City University of Hong Kong; (3) we studied the hotspots of SMBD in recent years, and realized the summary of the frontier of SMBD based on the keywords and co-citation literature, including the deep excavation and construction of social media technology, the reflection and concerns about the rapid development of social media, and the role of SMBD in solving human social development problems. These studies could provide values and references for SMBD researchers to understand the research status, hotspots and trends in this field.


2000 ◽  
Vol 49 (1) ◽  
pp. 25-33
Author(s):  
Debal C. Kar ◽  
Partha Bhattacharya

2019 ◽  
Vol 11 (6) ◽  
pp. 1580 ◽  
Author(s):  
Shan Du ◽  
Hua Li

With the advance of 5G communication technologies and Internet+ strategy, mobile commerce has experienced rapid growth and needs urgent attention from researchers. It is the aim of this article to analyze the literature on mobile commerce to address the following question: With the wide application of artificial intelligence and big data, what are the latest technology, models and problems in the background of the new era that researchers and practitioners need to understand in order to grasp the research frontier in this field quickly? Therefore, to achieve these objectives, this paper reviews 1130 m-commerce articles with 25,502 associated references from the SCI-EXPANDED, SSCI, CPCI-S, CPCI-SSH database and develops a framework of m-commerce value by analyzing the most influential authors, institutions, countries, journals and keywords in m-commerce. We apply three types of knowledge mapping to our study—cluster view, timezone view and timeline view. Frequency statistics, clustering coefficient as well as centrality calculation are employed to analyze by CiteSpace. We use the strength of citation bursts to analyze keywords and put result into the I-Modelwhich provide an important framework for classifying m-commerce activities and theories. In this study, we explore the knowledge structure, development and the future trend of mobile commerce for researchers. We identify the main technology and models to improve customer satisfaction and adoption behavior in the background of the new era which provide decision support for practitioners. Compared with the existing literature reviews of mobile commerce, we make a set of knowledge maps to show the future trend of mobile commerce and analyze visual results based on I-model. It is the first study to present the major clusters to reveal their associated intellectual bases and research fronts.


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