A Bibliometric Analysis of Drought Indices, Risk, and Forecast as Components of Drought Early Warning Systems

In this study, we apply a bibliometric analysis to characterize publication data on droughts, mainly focusing on drought indices (DIs), drought risk (DR), and drought forecast (DF). Data on publications on these selected topics were obtained through the Scopus database, covering the period from 1963 to June 2021. The DI-related publications, based on meteorological, soil moisture, hydrological, remote sensing, and composite/modeled Dis, accounted for 57%, 8%, 4%, 29%, and 2% of the scientific sources, respectively. DI-related studies showed a notable increase since the 1990s, due perhaps to a higher number of major droughts during the last three decades. It was found that USA and China were the two leading countries in terms of publication count and academic influence on the DI, DR, and DF studies. A network analysis of the country of residence of co-authors on DR and DF research highlighted the top three countries, which were the USA, China, and the United Kingdom. The most productive journal for the DI studies was found to be the International Journal of Climatology, whereas Natural Hazards was identified as the first-ranked journal for the DR and DF studies. In relation to individual researchers, Singh VP from the USA was found to be the most prolific author, having the greatest academic influence on DF study, whereas Zhang Q from China was identified as the most productive author on DR study. This bibliometric analysis reveals that further research is needed on droughts in the areas of risk management, water management, and drought management. This review maps trends of previous research in drought science, covering several important aspects, such as drought indices, geographic regions, authors and their collaboration paths, and sub-topics of interest. This article is expected to serve as an index of the current state of knowledge on drought warning systems and as guidance for future research needs.

Comparison of Altmetrics with Conventional Bibliometrics in the Surgical Literature (Preprint)

BACKGROUND The impact of a research publication has traditionally been quantified by its citation count. Newer bibliometric indices such as Altmetric Attention Score (AAS) and article page views are emerging as supplementary measures to quantify the academic influence of research. OBJECTIVE The aim of the current study was to interrogate the relationship between novel and traditional bibliometric indices for research published in a leading surgical journal and evaluate the role of these newer indices in measuring the impact of surgical research. METHODS All articles published in JAMA Surgery between 1 January 2019 and 1 September 2021 were examined. The literature database PubMed was used to identify all articles published within the specified time period. The cumulative citation count, AAS, and article page views were retrieved from the journal website. Statistical analysis using the Pearson rank correlation coefficient (r) was performed on Minitab 19. RESULTS : A total of 1,071 articles were retrieved for further analysis. The correlation (95% CI) between ranks for all articles was 0.396 (0.344-0.445) for AAS and citation scores, 0.541 (0.497-0.582) for citations and article page views, and 0.413 (0.362-0.461) for AAS and article page views. CONCLUSIONS We demonstrated a medium correlation between citations and AAS for articles published in a leading surgical journal. The inter-year correlation between 2019 and 2021 was similar, suggesting that AAS could be predictive of future citations. AAS may be useful in evaluating the wider societal impact of the surgical literature and could serve to promote greater public engagement in surgical research.

Analysis of the Characteristics and Influence Factors of High-Impact Papers that Common Concern to Researchers and the Public

The analysis of the evolution of the distribution characteristics of “high-impact papers,” which are highly concerned by researchers and the public, and their influence on academic and social factors, provides a reference for the combination of Altmetrics index and traditional literature measurement index in scientific research evaluation. Selecting 2015 to 2019 Altmetrics TOP100 papers, which are also highly cited papers in Web of Science as the “high-impact papers” data set. This paper explores the basic characteristics of high-impact papers and the influencing factors of Altmetrics indicators on academia and society by using basic statistical methods and SPSS. The results show that high-impact papers mainly come from international authoritative journals in natural science and biomedical categories with higher influence factors; there are more researches on medical and health sciences in high-impact papers, followed by earth and environmental sciences and human society studies; paid acquisition is the main way to obtain high-impact papers, but the proportion of open or free access to papers is increasing; News, Twitter and Blogs are the main ways to spread high-impact papers on social media, Mendeley, Blogs and Facebook have a certain correlation with the academic influence of papers, and Mendeley is the main factor influencing the academic influence. Combining traditional measurement index with Altmetrics index can evaluate the influence of the paper in multiple dimensions more objectively.

Relationships between Scientific Collaboration Ego Network and Academic Influence: An Empirical Examination of Intelligence Science Scholar in China

In this study, the author collaboration network is established by taking the national social science fund papers in the field of intelligence science included in CSSCI as the data source and the paper collaboration relationship of high-yielding authors as the research object. The connection structure and influence of nodes in the network are analyzed by using the Ego-network analysis method, and the network size, intensity, density of high-yielding author ego-network and the relationship with the influence of academic influence of researchers are found out. Measures of academic influence were also validated analytically. The size of collaboration network and the strength of connection between network members of researchers are positively correlated with academic influence, and there is an inverted U-shaped relationship between network density and academic influence. Finally, this study proposes suggestions on how researchers can strengthen academic collaboration to enhance academic influence.

Competitive Ranking of Six Major Tea-Related Research Organizations Through Bibliometric Analysis of Publications and Patents

Technological advances in tea production are critical to meet global demands for tea consumption. To illuminate differences in the scientific and commercial relevance of research programs between major tea-related research organizations around the world, we conducted a bibliometric analysis comparing the scientific outputs, including peer-reviewed publications and patents, of six major research organizations published between January 01, 2008 and July 11, 2020. For this competitive ranking analysis, we examined a number of papers, research topics, academic influence, capacity for development, capacity for collaboration, and capacity for technological innovation. Among the six research organizations, Anhui Agricultural University (in China) had the most publications, while the Chinese Academy of Agricultural Sciences, Tea Research Institute showed a higher capacity for development. The Council for Scientific and Industrial Research (in India) and the University of Shizuoka (Japan) both showed high academic influence, while the University of Shizuoka, Tea Research Association Tocklai and National Agriculture and Food Research Organization (Japan) showed a high capacity for collaboration. The Chinese Academy of Agricultural Sciences, Tea Research Institute applied for the most patents, while the Council for Scientific and Industrial Research applied for the most international patents.

The weighted impact factor: the paper evaluation index based on the citation ratio

PurposeThis study distinguishes the academic influence of different papers published in journals of the same subject or field based on the modification of the journal impact factor.Design/methodology/approachTaking SSCI journals in library and information science (LIS) as the research object, the authors first explore the skewness degree of the citation distribution of journal articles. Then, we define the paper citation ratio as the weight of impact factor to modify the journal impact factor for the evaluation of papers, namely the weighted impact factor. The authors further explore the feasibility of the weighted impact factor in evaluating papers.FindingsThe research results show that different types of skewness exist in the citation distribution of journal papers. Particularly, 94% of journal paper citations are highly skewed, while the rest are moderately skewed. The weighted impact factor has a closer correlation with the citation frequency of papers than the journal impact factor. It resolves the issue that the journal impact factor tends to exaggerate the influence of low-cited papers in journals with high impact factors or weaken the influence of high-cited papers in journals with low impact factors.Originality/valueThe weighted impact factor is constructed based on the skewness of the citation distribution of journal articles. It provides a new method to distinguish the academic influence of different papers published in journals of the same subject or field, then avoids the situation that papers published in the same journal having the same academic impact.