Objectives: Both citations and Altmetrics are indexes of influence of a publication, potentially useful, but to what extent that the professional-academic citation and media-dominated Altmetrics are consistent with each other is a topic worthy of being investigated. The objective is to show their correlation. Methods: DOI and citation information of COVID-19 researches were obtained from the Web of Science, its Altmetric indicators were collected from the Altmetrics. Correlation between the immediacy of citation and Altmetrics of COVID-19 research was studied by artificial neural networks. Results: Pearson coefficients are 0.962, 0.254, 0.222, 0.239, 0.363, 0.218, 0.136, 0.134, and 0.505 (p<0.01) for dimensions citation, attention score, journal impact factor, news, blogs, Twitter, Facebook, video, and Mendeley correlated with the SCI citation, respectively. The citations from the Web of Science and that from the Altmetrics have deviance large enough in the current. Altmetric score isn’t precise to describe the immediacy of citations of academic publication in COVID-19 research. Conclusions: The effects of news, blogs, Twitter, Facebook, video, and Mendeley on SCI citations are similar to that of the journal impact factor. This paper performs a pioneer study for investigating the role of academic topics across Altmetric sources on the dissemination of scholarly publications.

BACKGROUND: Although scholarly publishing plays a key role in learning, the role of knowledge translation of scholarly publishing with education and income on public health has not been well established. The objective was to describe how knowledge translation of scholarly publishing impacts on public health. METHODS: The correlations between the input data and the target data were firstly calculated. After the input data that is not correlated to the target have been removed, the principal component analysis will be performed to avoid multicollinearity problems in the input data. Finally, the multivariate regression method is used to fit the relationship between the principal components and the target data. Thus both dimensionality reduction and personalized optimization oriented a target can be done.RESULTS: After the public health in China is measured by Life expectancy and Death rate, the Pearson correlation coefficient, principal component analysis, and linear regression method have been performed. It proved that some activities of knowledge translation of scholarly publishing with a focus on health and well-being have the highest correlations with the first principal component. Results are also presented on that the first and the second principal component explain 99.3% of the variation (p<0.01) in Life expectancy and 92.8 % of the variation (p<0.01) in Death rate, respectively. CONCLUSIONS: Scholarly publishing, education, income, health expenditure, nurses, and midwives appear to have a similarly important effect on public health.

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Background. Knowledge can give an important contribution to local economic development, but the correlation between library activities and local economic development has not been clarified yet. The purpose of this investigation is to discuss the correlations between library output measures and regional economic measures.Methodology. The raw data obtained via the website of the National Bureau of Statistics of China have been analyzed by correlation coefficient calculations and multivariate regressions.  Results and discussion. It was found that there are significant positive correlations between the data of the regional public libraries such as the collections of public libraries owned per person, the total number of circulation of public libraries, the Number of Seats of Reading Room in Public Libraries, the Floor Space of Buildings of Public Libraries Owned per 10000 Population, the Number of Lectures in Public Libraries and the data of their economic development. Linear relationships between library activities and the gross regional product of the five provinces in China and one of China’s direct-controlled municipalities were observed after multivariate regressions were performed on the data.Conclusions. It can be concluded that economic development can benefit the development of libraries, and better education or a more educated population has resulted in more library use. The correlation analysis and multivariate regression analysis can be developed as a new way to measure the societal value of public libraries orientated for economic development or other targets.

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It is well known that knowledge is the source of modern economic growth, but the roles of library and information services on sustainable economic growth had not been well established. Thus, a case investigation was designed to identify the roles of library services in public libraries with the population, education, and income as a comparison on sustainable regional economic development. Such an investigation was based on organically combining correlation calculation, principal component calculation, and linear regression calculation. Results prove that some library services in public libraries have the highest contribution to the first principal component. It also demonstrates that the first principal component explains 85.0%, 95.0%, and 64.2% of the variation in the normalized gross regional products of Jiangsu Province, Hunan Province, and Gansu Province in China, respectively. Library services in public libraries, the population, education, and income appear to have a similarly important effect on sustainable regional development. Component score coefficients and linear relationships between the principal components and regional gross regional product can be used together to investigate the relationship between library services and sustainable economic growth. The proposed method provides new ideas for evaluating the roles of library services in sustainable economic growth.