A TOPSIS model for understanding the authors choice of journal selection

Characteristics analysis and evaluation of discourse leading for academic journals: perspectives from multiple integration of altmetrics indicators and evaluation methods

Purpose

Under the background of open science, this paper integrates altmetrics data and combines multiple evaluation methods to analyze and evaluate the indicators' characteristics of discourse leading for academic journals, which is of great significance to enrich and improve the evaluation theory and indicator system of academic journals.

Design/methodology/approach

This paper obtained 795,631 citations and 10.3 million altmetrics indicators data for 126,424 published papers from 151 medicine, general and internal academic journals. In this paper, descriptive statistical analysis and distribution rules of evaluation indicators are first carried out at the macro level. The distribution characteristics of evaluation indicators under different international collaboration conditions are analyzed at the micro level. Second, according to the characteristics and connotation of the evaluation indicators, the evaluation indicator system is constructed. Third, correlation analysis, factor analysis, entropy weight method and TOPSIS method are adopted to evaluate and analyze the discourse leading in medicine, general and internal academic journals by integrating altmetrics. At the same time, this paper verifies the reliability of the evaluation results.

Findings

Six features of discourse leading integrated with altmetrics indicators are obtained. In the era of open science, online academic exchanges are becoming more and more popular. The evaluation activities based on altmetrics have fine-grained and procedural advantages. It is feasible and necessary to integrate altmetrics indicators and combine the advantages of multiple methods to evaluate the academic journals' discourse leading of which are in a diversified academic ecosystem.

Originality/value

This paper uses descriptive statistical analysis to analyze the distribution characteristics and distribution rules of discourse leading indicators of academic journals and to explore the availability of altmetrics indicators and the effectiveness of constructing an evaluation system. Then, combining the advantages of multiple evaluation methods, The author integrates altmetrics indicators to comprehensively evaluate the discourse leading of academic journals and verify the reliability of the evaluation results. This paper aims to provide references for enriching and improving the evaluation theory and indicator system of academic journals.

Measuring knowledge contribution performance of physicians in online health communities: A BP neural network approach

Extant literature on measuring the performance of physicians’ knowledge contribution in an online health community (OHC) is limited. To address this gap, this article aims to (1) develop a measurement model for physicians’ knowledge contribution performance; (2) use BP neural network to assign reasonable weight to each indicator of the model; and (3) explore the status and differences of knowledge contribution performance among a group of physicians. Based on the sample of 5407 infectious disease physicians in a Chinese OHC, we propose the measurement model by integrating physicians’ active knowledge contribution (AKC) and responsive knowledge contribution (RKC), covering 11 dimensions of contribution quantity and quality. We employ the BP neural network to optimise the model weights using the initial weight of the model obtained by the entropy method. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to evaluate the performance of physicians’ knowledge contribution in the OHC. The results show that it is feasible to use BP neural network to assign model weights. The distribution of physicians’ knowledge contribution performance is uneven; only a few have a high-level knowledge contribution performance. Meanwhile, a significant positive correlation exists between a physician’s title and respective knowledge contribution performance. Our research may contribute to related literature and practices by offering a fine-grained understanding of the performance of physicians’ knowledge contribution.

Research on the discourse power evaluation of academic journals from the perspective of multiple fusion: Taking Medicine, General and Internal journals as an example

In the open science environment, this article evaluates the discourse power of academic journals from the perspective of multiple integration. It is conducive to scientific research management and provides a reference for enriching and perfecting the evaluation theory and indicators system of academic journals. Based on the theory of evaluation science, discourse power theory and communication theory, first, this article discusses the basic issues of the discourse power evaluation for academic journals. It defines the academic discourse power and the discourse power of academic journals. It is proposed that the discourse power of academic journals is composed of discourse influence and discourse leading. Discourse influence is composed of discourse influence ability and discourse power, and discourse leading is composed of social media discourse, news and policy discourse, encyclopaedia discourse, peer-review discourse and video discourse leading. This article explores the formation process and operation mechanism of the discourse power for academic journals. Then, this article constructs the discourse power evaluation model of academic journals. Second, this article integrates multi-source heterogeneous data, then adopts correlation analysis, integrated factor analysis, entropy weight method, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and two-dimensional four-quadrant mapping method to conduct empirical research on the discourse power evaluation of Medicine, General and Internal journals from the perspectives of multi-dimensions, multi-factors, multi-indicators and multi-methods fusion. The results show that the research on the discourse power evaluation for academic journals based on the theory, method and application logic is practical, comprehensive and reliable.