Jointly valuing journal visibility and author citation count: An axiomatic approach

This paper proposes a simple, flexible, axiom-based mechanism for facilitating the comparison between a scholar's citation count and the visibility of the journals wherein the scholar's articles were published. The goal is to help research review bodies easily grasp the distinction these two forms of scholarly accomplishment and to provide a transparent way to articulate expectations about them to scholars. The approach is demonstrated using a widely applied and cooperative functional form that can reflect, via different parameter values, a wide range of possible beliefs about the relative merits of citation counts and journal visibility.     

Impact maturity times and citation time windows: The 2-year maximum journal impact factor

Journal metrics are employed for the assessment of scientific scholar journals from a general bibliometric perspective. In this context, the Thomson Reuters journal impact factors (JIFs) are the citation-based indicators most used. The 2-year journal impact factor (2-JIF) counts citations to one and two year old articles, while the 5-year journal impact factor (5-JIF) counts citations from one to five year old articles. Nevertheless, these indicators are not comparable among fields of science for two reasons: (i) each field has a different impact maturity time, and (ii) because of systematic differences in publication and citation behavior across disciplines. In fact, the 5-JIF firstly appeared in the Journal Citation Reports (JCR) in 2007 with the purpose of making more comparable impacts in fields in which impact matures slowly. However, there is not an optimal fixed impact maturity time valid for all the fields. In some of them two years provides a good performance whereas in others three or more years are necessary. Therefore, there is a problem when comparing a journal from a field in which impact matures slowly with a journal from a field in which impact matures rapidly. In this work, we propose the 2-year maximum journal impact factor (2M-JIF), a new impact indicator that considers the 2-year rolling citation time window of maximum impact instead of the previous 2-year time window. Finally, an empirical application comparing 2-JIF, 5-JIF, and 2M-JIF shows that the maximum rolling target window reduces the between-group variance with respect to the within-group variance in a random sample of about six hundred journals from eight different fields.     

Some comments on the journal weighted impact factor proposed by Habibzadeh and Yadollahie

In a recent paper in the Journal of Informetrics, Habibzadeh and Yadollahie [Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172] propose a journal weighted impact factor (WIF). Unlike the ordinary impact factor, the WIF of a journal takes into account the prestige or the influence of citing journals. In this communication, we show that the way in which Habibzadeh and Yadollahie calculate the WIF of a journal has some serious problems. Due to these problems, a ranking of journals based on WIF can be misleading. We also indicate how the problems can be solved by changing the way in which the WIF of a journal is calculated.     

Estimating the accuracies of journal impact factor through bootstrap

The journal impact factor (JIF) reported in journal citation reports has been used to represent the influence and prestige of a journal. Whereas the consideration of the stochastic nature of a statistic is a prerequisite for statistical inference, the estimation of JIF uncertainty is necessary yet unavailable for comparing the impact among journals. Using journals in the Database of Research in Science Education (DoRISE), the current study proposes bootstrap methods to estimate the JIF variability. The paper also provides a comprehensive exposition of the sources of JIF variability. The collections of articles in the year of interest and in the preceding years both contribute to JIF variability. In addition, the variability estimate differs depending on the way a database selects its journals for inclusion. In the bootstrap process, the nested structure of articles in a journal was accounted for to ensure that each bootstrap replication reflects the actual citation characteristics of articles in the journal. In conclusion, the proposed point and interval estimates of the JIF statistic are obtained and more informative inferences on the impact of journals can be drawn.     

Journal acceptance rates: A cross-disciplinary analysis of variability and relationships with journal measures

There are many indicators of journal quality and prestige. Although acceptance rates are discussed anecdotally, there has been little systematic exploration of the relationship between acceptance rates and other journal measures. This study examines the variability of acceptance rates for a set of 5094 journals in five disciplines and the relationship between acceptance rates and JCR measures for 1301 journals. The results show statistically significant differences in acceptance rates by discipline, country affiliation of the editor, and number of reviewers per article. Negative correlations are found between acceptance rates and citation-based indicators. Positive correlations are found with journal age. These relationships are most pronounced in the most selective journals and vary by discipline. Open access journals were found to have statistically significantly higher acceptance rates than non-open access journals. Implications in light of changes in the scholarly communication system are discussed.     

Regularity in the time-dependent distribution of the percentage of never-cited papers: An empirical pilot study based on the six journals

The non-citation rate refers to the proportion of papers that do not attract any citation over a period of time following their publication. After reviewing all the related papers in Web of Science, Google Scholar and Scopus database, we find the current literature on citation distribution gives more focus on the distribution of the percentages and citations of papers receiving at least one citation, while there are fewer studies on the time-dependent patterns of the percentage of never-cited papers, on what distribution model can fit their time-dependent patterns, as well as on the factors influencing the non-citation rate. Here, we perform an empirical pilot analysis to the time-dependent distribution of the percentages of never-cited papers in a series of different, consecutive citation time windows following their publication in our selected six sample journals, and study the influence of paper length on the chance of papers’ getting cited. Through the above analysis, the following general conclusions are drawn: (1) a three-parameter negative exponential model can well fit time-dependent distribution curve of the percentages of never-cited papers; (2) in the initial citation time window, the percentage of never-cited papers in each journal is very high. However, as the citation time window becomes wider and wider, the percentage of never-cited papers begins to drop rapidly at first, and then drop more slowly, and the total degree of decline for most of journals is very large; (3) when applying the wider citation time windows, the percentage of never-cited papers for each journal begins to approach a stable value, and after that value, there will be very few changes in these stable percentages, unless we meet a large amount of “Sleeping Beauties” type papers; (4) the length of an paper has a great influence on whether it will be cited or not.     

Microsoft Academic automatic document searches: Accuracy for journal articles and suitability for citation analysis

Microsoft Academic is a free academic search engine and citation index that is similar to Google Scholar but can be automatically queried. Its data is potentially useful for bibliometric analysis if it is possible to search effectively for individual journal articles. This article compares different methods to find journal articles in its index by searching for a combination of title, authors, publication year and journal name and uses the results for the widest published correlation analysis of Microsoft Academic citation counts for journal articles so far. Based on 126,312 articles from 323 Scopus subfields in 2012, the optimal strategy to find articles with DOIs is to search for them by title and filter out those with incorrect DOIs. This finds 90% of journal articles. For articles without DOIs, the optimal strategy is to search for them by title and then filter out matches with dissimilar metadata. This finds 89% of journal articles, with an additional 1% incorrect matches. The remaining articles seem to be mainly not indexed by Microsoft Academic or indexed with a different language version of their title. From the matches, Scopus citation counts and Microsoft Academic counts have an average Spearman correlation of 0.95, with the lowest for any single field being 0.63. Thus, Microsoft Academic citation counts are almost universally equivalent to Scopus citation counts for articles that are not recent but there are national biases in the results.     

Globalised vs averaged: Bias and ranking performance on the author level

We analyse the difference between the averaged (average of ratios) and globalised (ratio of averages) author-level aggregation approaches based on various paper-level metrics. We evaluate the aggregation variants in terms of (1) their field bias on the author-level and (2) their ranking performance based on test data that comprises researchers that have received fellowship status or won prestigious awards for their long-lasting and high-impact research contributions to their fields. We consider various direct and indirect paper-level metrics with different normalisation approaches (mean-based, percentile-based, co-citation-based) and focus on the bias and performance differences between the two aggregation variants of each metric. We execute all experiments on two publication databases which use different field categorisation schemes. The first uses author-chosen concept categories and covers the computer science literature. The second covers all disciplines and categorises papers by keywords based on their contents. In terms of bias, we find relatively little difference between the averaged and globalised variants. For mean-normalised citation counts we find no significant difference between the two approaches. However, the percentile-based metric shows less bias with the globalised approach, except for citation windows smaller than four years. On the multi-disciplinary database, PageRank has the overall least bias but shows no significant difference between the two aggregation variants. The averaged variants of most metrics have less bias for small citation windows. For larger citation windows the differences are smaller and are mostly insignificant.In terms of ranking the well-established researchers who have received accolades for their high-impact contributions, we find that the globalised variant of the percentile-based metric performs better. Again we find no significant differences between the globalised and averaged variants based on citation counts and PageRank scores.     

医学论文作者单位标注问题探讨

近年来,多作者、多单位署名已成为科技论文署名的新趋势.作者单位标注关系到论文责任单位的知识产权.研究生、进修医师论文发表、作者工作单位变更以及多单位间合作是出现作者单位标注不当的常见原因.期刊编辑加强对作者来稿的审查,提高作者的知识产权意识,有助于避免作者单位标注不当的发生.     

JCR五年期影响因子探析

使用期刊引证报告(JCR)6015种期刊数据,以统计学方法探索性地分析5年期影响因子IF5的特点.结果显示,IF5作为具有代表性的平均性期刊评价指标,能更好地反映多数期刊被引高峰,总体符合布拉德福分布.IF5与2年期影响因子IF存在排序相关,也有显著统计学差异,两者测评结果在较好和较差期刊上相对一致,但在多数水平居中的期刊上存在区别.最后,给出Ifa指数测度两种影响因子的差别和Ifb指数综合两种影响因子的评价信息.     

Normalization of zero-inflated data: An empirical analysis of a new indicator family and its use with altmetrics data

Recently, two new indicators (Equalized Mean-based Normalized Proportion Cited, EMNPC; Mean-based Normalized Proportion Cited, MNPC) were proposed which are intended for sparse scientometrics data, e.g., alternative metrics (altmetrics). The indicators compare the proportion of mentioned papers (e.g. on Facebook) of a unit (e.g., a researcher or institution) with the proportion of mentioned papers in the corresponding fields and publication years (the expected values). In this study, we propose a third indicator (Mantel-Haenszel quotient, MHq) belonging to the same indicator family. The MHq is based on the MH analysis – an established method in statistics for the comparison of proportions. We test (using citations and assessments by peers, i.e. F1000Prime recommendations) if the three indicators can distinguish between different quality levels as defined on the basis of the assessments by peers. Thus, we test their convergent validity. We find that the indicator MHq is able to distinguish between the quality levels in most cases while MNPC and EMNPC are not. Since the MHq is shown in this study to be a valid indicator, we apply it to six types of zero-inflated altmetrics data and test whether different altmetrics sources are related to quality. The results for the various altmetrics demonstrate that the relationship between altmetrics (Wikipedia, Facebook, blogs, and news data) and assessments by peers is not as strong as the relationship between citations and assessments by peers. Actually, the relationship between citations and peer assessments is about two to three times stronger than the association between altmetrics and assessments by peers.     

中印学术期刊的国际竞争力比较研究

中国和印度作为世界公认的亚洲两个实力较为接近的发展中国家,有必要对其在科技、政治、军事等领域的差异作进一步的分析,以取长补短。学术期刊可以体现一个国家的科研竞争力,同时也是科学生产率的重要表现形式之一。因此,比较中国和印度学术期刊的相关情况具有一定的现实意义。本文主要选取中国和印度均被《期刊引证报告》(Journal Citation Reports,JCR)收录的期刊,通过比较各个期刊的各项指标以及这些期刊所涵盖学科的基本情况,从而得出中国相对于印度在此类科技期刊上的优势和劣势,并通过比较和分析,得出相关结论。     

我国“图书馆、情报与文献学”图书学术影响力报告——基于CSSCI的分析

为考量我国"图书馆、情报与文献学"图书学术影响力的大小,本文借助<中文社会科学引文索引>(2000-2007)数据,利用引文分析法,对"图书馆、情报与文献学"学科论文引用的图书进行统计,推出该学科领域最有学术影响的137种国内外学术著作.研究发现,在各类型图书中,对图书馆、情报与文献学领域产生最大学术影响力的是国内学术著作;国外学术著作被引种数排在第二,但被引篇次和篇均被引次数都明显偏低,显示国外学术著作对本领域学术影响有限.     

On the relationship between download and citation counts: An introduction of Granger-causality inference

Studies on the relationship between the numbers of citations and downloads of scientific publications is beneficial for understanding the mechanism of citation patterns and research evaluation. However, seldom studies have considered directionality issues between downloads and citations or adopted a case-by-case time lag length between the download and citation time series of each individual publication. In this paper, we introduce the Granger-causal inference strategy to study the directionality between downloads and citations and set up the length of time lag between the time series for each case. By researching the publications on the Lancet, we find that publications have various directionality patterns, but highly cited publications tend to feature greater possibilities to have Granger causality. We apply a step-by-step manner to introduce the Granger-causal inference method to information science as four steps, namely conducting stationarity tests, determining time lag between time series, establishing cointegration test, and implementing Granger-causality inference. We hope that this method can be applied by future information scientists in their own research contexts.     

Regularity in the research output of individual scientists: An empirical analysis by recent bibliometric tools

This paper proposes an empirical analysis of several scientists based on their time regularity, defined as the ability of generating an active and stable research output over time, in terms of both quantity/publications and impact/citations. In particular, we empirically analyse three recent bibliometric tools to perform qualitative/quantitative evaluations under the new perspective of regularity. These tools are respectively (1) the PY/CY diagram, (2) the publication/citation Ferrers diagram and triad indicators, and (3) a year-by-year comparison of the scientists’ output (Borda's ranking). Results of the regularity analysis are then compared with those obtained under the classical perspective of overall production.The proposed evaluation tools can be applied to competitive examinations for research position/promotion, as complementary instruments to the commonly adopted bibliometric techniques.     

改版后的《大学图书情报学刊》

文章应用文献计量的方法对改版后的<大学图书情报学刊>(2002-2004)的来稿、载文、作者和引文进行了统计与分析,以求客观地评价<学刊>的成绩及不足,促进<学刊>可持续稳步发展.     

中文核心期刊要目总览和中国科学引文数据库期刊数据按学科类目的比较分析

按自然科学、医学卫生、农业科学及工业技术等4大类学科，对《中文核心期刊要目总览》所评定的核心期刊与《中国科学引文数据库（CSCD）》的源期刊进行统计、分析比较，揭示两者收录期刊学科分布的特性，指出将两者作为学术评估、期刊选定标准等评价工具时应注意的问题和适用的场合。     

Journal editorship index for assessing the scholarly impact of academic institutions: An empirical analysis in the field of economics

Assessing the scholarly impact of academic institutions has become increasingly important. The achievements of editorial board members can create benchmarks for research excellence and can be used to evaluate both individual and institutional performance. This paper proposes a new method based on journal editor data for assessing an institution’s scholarly impact. In this paper, a journal editorship index (JEI) that simultaneously accounts for the journal rating (JR), editor title (ET), and board size (BS) is constructed. We assess the scholarly impact of economics institutions based on the editorial boards of 211 economics journals (which include 8640 editorial board members) in the ABS Academic Journal Guide. Three indices (JEI/ET, JEI/JR, and JEI/BS) are also used to rank the institutions. It was found that there was only a slight change in the relative institutional rankings using the JEI/ET and JEI/BS compared to the JEI. The BS and ET weight factors did not have a substantial influence on the ranking of institutions. It was also found that the journal rating weight factor had a large effect on the ranking of institutions. This paper presents an alternative approach to using editorial board memberships as the basis for assessing the scholarly impact of economics institutions.     

引文的本质及其学术评价功能辨析

为准确理解和利用引文的评价功能,利用概念分析法和社会学原理,分析引文、念的异同,考察引文的含义和引文类型的多样性.以历史学、经济学和图书馆学引文为例,论证在一定条件下引文的有序性和层次性,探讨引文的本质及其一定的评价功能.笔者指出目前对引文评价功能的利用比较片面,并对编制专门的引文评价数据库和提高学术共同体学术理念与引用规范等提出建议.参考文献7.     

高品质论文被引数据及其对学术评价的启示

针对学术品质与学术影响的关系,以20世纪Nature上发表的内容获得过诺贝尔奖的13篇代表性论文作为高品质论文小样本,用IsI-ESI中有关学科最高被引论文数据作为定量参照,发现高品质论文不是最高被引论文,但都高于学科平均被引;而最高被引论文的品质不能肯定最优,但一般具有广泛影响.建议以双向匿名同行评议判断学术品质,以计量分析判断学术影响,综合学术品质和学术影响合成学术评价.表2.参考文献6.