Abstract: The standardization of altmetrics indicators is a crucial requirement for their application in scientific evaluation. This study targets the construction of a Chinese indigenous knowledge system, which focuses on WeChat mention data from Chinese academic papers. We used standardization methods based on relative citation methods and incorporated the WeChat Communication Index to establish standardized metrics for WeChat mentions. This research aims to provide relevant references and foundations for the development, deepening, and application of Chinese altmetrics data sources. Key findings include:(1) By eliminating time differences, disciplinary variations, high sparsity, and skewed distributions in WeChat mention metrics, the standardized indicators for WeChat mentions can be considered for application in academic evaluation and social impact assessment.(2) Within the WI(WeChat Index) journal set, philosophy and humanities, engineering II, and agricultural engineering are the top three disciplines with the highest number of WeChat mentions of academic papers.(3) WPP/FWSm and MNWS, metrics based on WeChat mention frequency, show minimal differences. These two indexes are suitable for evaluating WeChat attention at the level of individual papers and journals but are unsuitable for evaluating universities due to their influence by the distribution characteristics of WeChat mentions.(4) Standardized metrics, WCPP/FWSm and MNWC, incorporating WeChat influence indices, show a better balance between WeChat influence and mention volume. They demonstrate robustness and prove valuable for assessing WeChat attention at the individual paper, journal, and university levels. They are more effective in assessing the WeChat attention and the dissemination impact of academic papers in universities.

Key words: Altmetrics, WeChat official account, Altmetrics indicators, WeChat mention, Metric standardization