Search results

1 – 3 of 3
Per page
102050
Citations:
Loading...
Access Restricted. View access options
Article
Publication date: 6 August 2021

Shuai Zhang, Feicheng Ma, Yunmei Liu and Wenjing Pian

The purpose of this paper is to explore the features of health misinformation on social media sites (SMSs). The primary goal of the study is to investigate the salient features of…

1449

Abstract

Purpose

The purpose of this paper is to explore the features of health misinformation on social media sites (SMSs). The primary goal of the study is to investigate the salient features of health misinformation and to develop a tool of features to help users and social media companies identify health misinformation.

Design/methodology/approach

Empirical data include 1,168 pieces of health information that were collected from WeChat, a dominant SMS in China, and the obtained data were analyzed through a process of open coding, axial coding and selective coding. Then chi-square test and analysis of variance (ANOVA) were adopted to identify salient features of health misinformation.

Findings

The findings show that the features of health misinformation on SMSs involve surface features, semantic features and source features, and there are significant differences in the features of health misinformation between different topics. In addition, the list of features was developed to identify health misinformation on SMSs.

Practical implications

This study raises awareness of the key features of health misinformation on SMSs. It develops a list of features to help users distinguish health misinformation as well as help social media companies filter health misinformation.

Originality/value

Theoretically, this study contributes to the academic discourse on health misinformation on SMSs by exploring the features of health misinformation. Methodologically, the paper serves to enrich the literature around health misinformation and SMSs that have hitherto mostly drawn data from health websites.

Details

Library Hi Tech, vol. 40 no. 5
Type: Research Article
ISSN: 0737-8831

Keywords

Access Restricted. View access options
Article
Publication date: 4 March 2020

Yunmei Liu, Changling Li and Zichun Gao

With the development of Web2.0 and publishing digitalization, traditional libraries and evaluation citation system can no longer indicate academic paper influence validly…

504

Abstract

Purpose

With the development of Web2.0 and publishing digitalization, traditional libraries and evaluation citation system can no longer indicate academic paper influence validly. Therefore, it is necessary to construct smart library and find the evaluation effect of Internet metrics-Usage.

Design/methodology/approach

This study puts forward four indexes of scholars’ evaluation based on Usage (total Usage (U), average Usage rate (U/N), hu-index and pu-index), which refer to citation indexes, takes the 35 high-output scholars in the field of library and information science in the WoS database as examples, analyzes performance of different scholars evaluation indexes based on Usage and compares the differences and correlations between “citation indicators” and “usage indicators.”

Findings

This study results show that pu-index is the strongest index to evaluate scholars. Second, there is a high correlation and strong mechanism based on time dependence and interactions between Usage and citation. Third, compared to “citation indicators”, the “usage indicators” has a larger numerical value and wider measurement range, which can break the time limitation of citation, and scientifically evaluate young scholars and newly published paper by scholars.

Originality/value

This paper proposes the pu-index – a relatively superior mathematical model for Usage and provides reference for the scholars’ evaluation policy of the smart library. This model can not only provide fair evaluation conditions for young scientists but also shorten the evaluation effect of the time lag of cited indicators. In addition, the “usage indicators” in this paper are new scientific evaluation indicators generated in the network environment. Applying it to the academic evaluation system will make the research papers widely accepted by the public and will also encourage scientists to follow the development of the Internet age and pursue research with equal emphasis on quantity and quality.

Details

Library Hi Tech, vol. 40 no. 1
Type: Research Article
ISSN: 0737-8831

Keywords

Access Restricted. View access options
Article
Publication date: 27 April 2020

Yingying Zheng and Shuang Liu

In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the…

769

Abstract

Purpose

In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the topic–author–citation based on the z index and proposes the ZAS index to evaluate scholars on different research topics within the discipline.

Design/methodology/approach

Based on the sample data of the CSSCI journals in the discipline of physical education in the past five years, the keywords were classified into 13 categories of research topics including female sports. The ZAS index of scholars on topic of female sports and so on was calculated, and quantitative indexes such as h index p index and z index were calculated. Comparative analysis of the evaluation effect was performed.

Findings

It is found that compared with the h index and p index, the z index achieves a better balance between the quantity, quality and citation distribution of scholars' results and effectively recognizes that the citation quality is higher and the number of citations of each paper is more balanced. In addition, compared to the z index, this article is based on a ZAS index model with an improved three-dimensional topic–author–citation relationship in research fields such as female sports.

Originality/value

It can identify some outstanding scholars who are engaged in small-scale or emerging topic research such as female sports and are excellent in different research areas. Talents create an objective and fair evaluation environment. At the same time, the ranking ability of ZAS indicators in the evaluation of talents is the strongest, and it is expected to be used in practical evaluations.

Details

Library Hi Tech, vol. 40 no. 1
Type: Research Article
ISSN: 0737-8831

Keywords

1 – 3 of 3
Per page
102050