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| Comprehensive Analysis of Data Characteristics in Chinese Academic Papers Mentioned on WeChat |
| Yu Houqiang1, Li Longfei2,3, Yang Siluo2,3 |
1.School of Information Management, Sun Yat-sen University, Guangzhou 510006
2.School of Information Management, Wuhan University, Wuhan 430072
3.Research Center for Chinese Science Evaluation (RCCSE), Wuhan University, Wuhan 430072 |
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Abstract Research on the development and application of Chinese altmetric data is limited. This study aims to contribute to the construction of China’s independent knowledge system by investigating the distribution characteristics of numerical values associated with Chinese academic papers mentioned on WeChat. This study presents the distribution characteristics of WeChat mention indicators of all the Chinese academic papers mentioned on WeChat and included in the China National Knowledge Infrastructure (CNKI) in January 2021. The presentation form and timeliness were analyzed along with paper, source, and discipline levels using statistical analysis and data visualization. The main finding of this study is that non-referenced literature accounts for 60.80% of WeChat mentions. Second, the timeliness of WeChat mentions was 56.56%, mainly because scholars shared their research findings at conferences and lectures. Third, the Chinese academic papers mentioned on WeChat official accounts are diverse and scattered. Papers published in core journals are more likely to be mentioned, and the WeChat accounts of journals exhibit noticeable self-mention behavior. Fourth, mentions of academic papers can enhance the professionalism and authority of WeChat articles, promoting their dissemination along with research results, thereby increasing their social impact.
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Received: 19 December 2023
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