Effect of publication month on citation impact

A standard procedure in citation analysis is that all papers published in one year are assessed at the same later point in time, implicitly treating all publications as if they were published at the exact same date. This leads to systematic bias in favor of early-months publications and against late-months publications. This contribution analyses the size of this distortion on a large body of publications from all disciplines over citation windows of up to 15 years. It is found that early-month publications enjoy a substantial citation advantage, which arises from citations received in the first three years after publication. While the advantage is stronger for author self-citations as opposed to citations from others, it cannot be eliminated by excluding self-citations. The bias decreases only slowly over longer citation windows due to the continuing influence of the earlier years’ citations. Because of the substantial extent and long persistence of the distortions, it would be useful to remove or control for this bias in research and evaluation studies which use citation data. It is demonstrated that this can be achieved by using the newly introduced concept of month-based citation windows.     

The problem of citation impact assessments for recent publication years in institutional evaluations

Bibliometrics has become an indispensable tool in the evaluation of institutions (in the natural and life sciences). An evaluation report without bibliometric data has become a rarity. However, evaluations are often required to measure the citation impact of publications in very recent years in particular. As a citation analysis is only meaningful for publications for which a citation window of at least three years is guaranteed, very recent years cannot (should not) be included in the analysis. This study presents various options for dealing with this problem in statistical analysis. The publications from two universities from 2000 to 2011 are used as a sample dataset (n = 2652, univ 1 = 1484 and univ 2 = 1168). One option is to show the citation impact data (percentiles) in a graphic and to use a line for percentiles regressed on ‘distant’ publication years (with confidence interval) showing the trend for the ‘very recent’ publication years. Another way of dealing with the problem is to work with the concept of samples and populations. The third option (very related to the second) is the application of the counterfactual concept of causality.     

An empirical approach based on quantile regression for estimating citation ageing

An aspect of citation behavior, which has received longstanding attention in research, is how articles’ received citations evolve as time passes since their publication (i.e., citation ageing). Citation ageing has been studied mainly by the formulation and fit of mathematical models of diverse complexity. Commonly, these models restrict the shape of citation ageing functions and explicitly take into account factors known to influence citation ageing. An alternative—and less studied—approach is to estimate citation ageing functions using data-driven strategies. However, research following the latter approach has not been consistent in taking into account those factors known to influence citation ageing. In this article, we propose a model-free approach for estimating citation ageing functions which combines quantile regression with a non-parametric specification able to capture citation inflation. The proposed strategy allows taking into account field of research effects, impact level effects, citation inflation effects and skewness in the distribution of cites effects. To test our methodology, we collected a large dataset consisting of more than five million citations to 59,707 research articles spanning 12 dissimilar fields of research and, with this data in hand, tested the proposed strategy.     

The landmark citation method: analysis of a citation pattern as a collection assessment method.

The landmark citation method is a new collection assessment method based on the citation record of a single landmark article. This citation record is developed by identifying sources which cite the landmark article. A bibliography, extracted from the citation record, is then used to complete an assessment of the collection. This method was developed and used to assess the biotechnology collection of the National Library of Medicine. The information gained from this study, in addition to demonstrating the technique, also provided insight into the evolution of the biotechnology literature.     

基于Web2.0的图书馆建设研究综述

文章对近三年发表的Web2．0在图书馆中的研究与应用的全部文献进行了分析与归纳，从Web2．0概念及涵义、图书馆2．0的基本理念与原则、Web2．0技术应用研究、Web2．0创新图书馆服务模式的思考等方面对Web2．0在图书馆的应用进行了综述，旨在数字图书馆的建设中引入新理念、新技术、新应用，使数字图书馆的服务方式与技术手段能更好地适应新环境的变化，使图书馆在信息万变的大潮中永立不败之地。     

Algorithmically generated subject categories based on citation relations: An empirical micro study using papers on overall water splitting

One important reason for the use of field categorization in bibliometrics is the necessity to make citation impact of papers published in different scientific fields comparable with each other. Raw citations are normalized by using field-categorization schemes to achieve comparable citation scores. There are different approaches to field categorization available. They can be broadly classified as intellectual and algorithmic approaches. A paper-based algorithmically constructed classification system (ACCS) was proposed which is based on citation relations. Using a few ACCS field-specific clusters, we investigate the discriminatory power of the ACCS. The micro study focusses on the topic ‘overall water splitting’ and related topics. The first part of the study investigates intellectually whether the ACCS is able to identify papers on overall water splitting reliably and validly. Next, we compare the ACCS with (1) a paper-based intellectual (INSPEC) classification and (2) a journal-based intellectual classification (Web of Science, WoS, subject categories). In the last part of our case study, we compare the average number of citations in selected ACCS clusters (on overall water splitting and related topics) with the average citation count of publications in WoS subject categories related to these clusters. The results of this micro study question the discriminatory power of the ACCS. We recommend larger follow-up studies on broad datasets.     

An index for evaluating journals in a small domestic citation index database whose citation rate is generally very low: A test based on the Korea Citation Index (KCI) database

This study describes the meaning of and the formula for S-index, which is a novel evaluation index based on the number of citations of each article in a particular journal and the rank of the article according to the number of citations. This study compares S-index with Impact Factor (IF), which is the most well-known evaluation index, using the Korea Citation Index data. It is shown that S-index is positively correlated with the number of articles published in a journal. Tapered h-index (h_T-index), which is based on all articles of a journal like S-index, is compared with S-index. It is shown that there is a very strong positive correlation between S-index and h_T-index. Although S-index is similar to h_T-index, S-index has a slightly better differentiating power and ranks the journal with evenly cited articles higher.     

Regression for citation data: An evaluation of different methods

Citations are increasingly used for research evaluations. It is therefore important to identify factors affecting citation scores that are unrelated to scholarly quality or usefulness so that these can be taken into account. Regression is the most powerful statistical technique to identify these factors and hence it is important to identify the best regression strategy for citation data. Citation counts tend to follow a discrete lognormal distribution and, in the absence of alternatives, have been investigated with negative binomial regression. Using simulated discrete lognormal data (continuous lognormal data rounded to the nearest integer) this article shows that a better strategy is to add one to the citations, take their log and then use the general linear (ordinary least squares) model for regression (e.g., multiple linear regression, ANOVA), or to use the generalised linear model without the log. Reasonable results can also be obtained if all the zero citations are discarded, the log is taken of the remaining citation counts and then the general linear model is used, or if the generalised linear model is used with the continuous lognormal distribution. Similar approaches are recommended for altmetric data, if it proves to be lognormally distributed.     

Use of faculty publication lists and ISI citation data to identify a core list of journals with local importance

A method was developed to rank journals in a specific subject area, molecular and cellular biology (MCB), in order to create a core list of journals for the MCB faculty of the Pennsylvania State University. The core list of journals was needed as the first step in a larger serials evaluation process. The method did not require use data, but incorporated various quality measures, including publication in journals by Penn State faculty, citings of journals by Penn State faculty, and Journal Citation Report data from ISI. This study produced a core list of 50 MCB journals, as well as other benefits. Although the list of core MCB journals derived from this study is specific to the needs of Penn State faculty, the method could be adapted to other situations.     

The influences of counting methods on university rankings based on paper count and citation count

In an age of intensifying scientific collaboration, the counting of papers by multiple authors has become an important methodological issue in scientometric based research evaluation. Especially, how counting methods influence institutional level research evaluation has not been studied in existing literatures. In this study, we selected the top 300 universities in physics in the 2011 HEEACT Ranking as our study subjects. We compared the university rankings generated from four different counting methods (i.e. whole counting, straight counting using first author, straight counting using corresponding author, and fractional counting) to show how paper counts and citation counts and the subsequent university ranks were affected by counting method selection. The counting was based on the 1988–2008 physics papers records indexed in ISI WoS. We also observed how paper and citation counts were inflated by whole counting. The results show that counting methods affected the universities in the middle range more than those in the upper or lower ranges. Citation counts were also more affected than paper counts. The correlation between the rankings generated from whole counting and those from the other methods were low or negative in the middle ranges. Based on the findings, this study concluded that straight counting and fractional counting were better choices for paper count and citation count in the institutional level research evaluation.     

编委推荐制:保证期刊论文学术水平的一种举措

<应用数学和力学>的办刊实践表明,编委推荐制是保证期刊论文学术水平的一种有效举措.它对稿件的判断更为科学,稿件处理和发表更为及时、快捷,有利于发现和培养年轻科学家和推动学科的发展.     

A comparative study of cross-domain research output and citations: Research impact cubes and binary citation frequencies

Across the various scientific domains, significant differences occur with respect to research publishing formats, frequencies and citing practices, the nature and organisation of research and the number and impact of a given domain's academic journals. Consequently, differences occur in the citations and h-indices of the researchers. This paper attempts to identify cross-domain differences using quantitative and qualitative measures. The study focuses on the relationships among citations, most-cited papers and h-indices across domains and for research group sizes. The analysis is based on the research output of approximately 10,000 researchers in Slovenia, of which we focus on 6536 researchers working in 284 research group programmes in 2008–2012.As comparative measures of cross-domain research output, we propose the research impact cube (RIC) representation and the analysis of most-cited papers, highest impact factors and citation distribution graphs (Lorenz curves). The analysis of Lotka's model resulted in the proposal of a binary citation frequencies (BCF) distribution model that describes well publishing frequencies. The results may be used as a model to measure, compare and evaluate fields of science on the global, national and research community level to streamline research policies and evaluate progress over a definite time period.     

Publication point indicators: A comparative case study of two publication point systems and citation impact in an interdisciplinary context

The paper presents comparative analyses of two publication point systems, The Norwegian and the in-house system from the interdisciplinary Danish Institute of International Studies (DIIS), used as case in the study for publications published 2006, and compares central citation-based indicators with novel publication point indicators (PPIs) that are formalized and exemplified. Two diachronic citation windows are applied: 2006-07 and 2006-08. Web of Science (WoS) as well as Google Scholar (GS) are applied to observe the cite delay and citedness for the different document types published by DIIS, journal articles, book chapters/conference papers and monographs. Journal Crown Indicator (JCI) calculations was based on WoS. Three PPIs are proposed: the Publication Point Ratio (PPR), which measures the sum of obtained publication points over the sum of the ideal points for the same set of documents; the Cumulated Publication Point Indicator (CPPI), which graphically illustrates the cumulated gain of obtained vs. ideal points, both seen as vectors; and the normalized Cumulated Publication Point Index (nCPPI) that represents the cumulated gain of publication success as index values, either graphically or as one overall score for the institution under evaluation.The case study indicates that for smaller interdisciplinary research institutions the cite delay is substantial (2–3 years to obtain a citedness of 50%) when applying WoS for articles. Applying GS implies a shorter delay and much higher citedness for all document types. Statistical significant correlations were only found between WoS and GS and the two publication point systems in between, respectively. The study demonstrates how the nCPPI can be applied to institutions as evaluation tools supplementary to JCI in various combinations, in particular when institutions include humanistic and social science disciplines.     

基于引文的科技期刊相互影响力指标初探

提出科技期刊相互影响力的概念.科技期刊相互影响力,是指基于一定时间段内2种期刊之间相互引用频次统计量的比值来衡量其相互之间学术影响力的大小.简述科技期刊相互影响力评价指标计算方法,指出科技期刊相互影响力分析评价的目的和意义,并提出相关建议.     

Testing the fairness of citation indicators for comparison across scientific domains: The case of fractional citation counts

Citation numbers are extensively used for assessing the quality of scientific research. The use of raw citation counts is generally misleading, especially when applied to cross-disciplinary comparisons, since the average number of citations received is strongly dependent on the scientific discipline of reference of the paper. Measuring and eliminating biases in citation patterns is crucial for a fair use of citation numbers. Several numerical indicators have been introduced with this aim, but so far a specific statistical test for estimating the fairness of these numerical indicators has not been developed. Here we present a statistical method aimed at estimating the effectiveness of numerical indicators in the suppression of citation biases. The method is simple to implement and can be easily generalized to various scenarios. As a practical example we test, in a controlled case, the fairness of fractional citation count, which has been recently proposed as a tool for cross-discipline comparison. We show that this indicator is not able to remove biases in citation patterns and performs much worse than the rescaling of citation counts with average values.     

The influence of the PSI directive on open government data: An overview of recent developments

This paper looks at the role of the European Directive on re-use of public sector information in the current trend towards opening up government data. After discussing the PSI directive, it gives an overview of current policies and practices with regard to open government data in the Member States. It is argued that the success of the open government data movement in some Member States can be related to the confusion or ignorance about the relationship between traditional freedom of information legislation and the re-use of public sector data. If future information policies decide to follow this trend, they should always ensure that existing rights on freedom of information are not harmed.