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1.
[目的/意义]探索中文学术期刊论文的引文模式及时间窗口的选择对引文模式的影响，建立引文模式的分析框架。[方法/过程]以2006-2008年出版的图书情报领域期刊论文作为研究对象，采用两步聚类法对单篇论文在7年内的绝对被引量与相对被引量进行聚类分析，研究论文主要特征因子与引文模式的相关性。[结果/结论]在绝对被引量视角下，期刊论文均表现为先上升后下降的经典引文模式；在相对下载量视角下，期刊论文共有6种引文模式，其中3种可以归纳为经典引文模式，另外3种分别为"类睡美人型"、正偏型和马拉松型。相对被引量视角下，首年被引量与总被引量呈现了中等甚至较强的相关性，并且平均被引量越高，相关性越强，绝对被引量视角下的结果正好相反。结果表明，期刊论文的初始被引量与总被引量的相关性高低主要取决于引文曲线的峰度而非总被引量的大小。 相似文献
2.
Using 17 open-access journals published without interruption between 2000 and 2004 in the field of library and information science, this study compares the pattern of cited/citing hyperlinked references of Web-based scholarly electronic articles under various citation ranges in terms of language, file format, source and top-level domain. While the patterns of cited references were manually examined by counting the live hyperlinked-cited references, the patterns of citing references were examined by using the cited by tag in Google Scholar. The analysis indicates that although language, top-level domain, and file format of citations did not differ significantly for articles under different citation ranges, sources of citation differed significantly for articles in different citation ranges. Articles with fewer citations mostly cite less-scholarly sources such as Web pages, whereas articles with a higher number of citations mostly cite scholarly sources such as journal articles, etc. The findings suggest that 8 out of 17 OA journals in LIS have significant research impact in the scholarly communication process. 相似文献
3.
科学研究的目的在于创造知识,并应用理论成果解决我国社会、经济、文化等发展中的实际问题。将论文发表在国际期刊上可以让更多的国际同行了解我国最新的科研成果,为我国获得更多的国际影响力,所以在过去二十多年里SCI论文成为我国科研考核的一个重要指标。在这种科研评价导向下,我国学者发表的国际论文数量已居世界第一位,而大量来自国内同行的引用使得我国国际论文的被引量排名世界第二。本文提取1990至2015年Web of Science论文及其引文的数据,分析不同国家、不同学科在国家层次的自引情况,并在不同国家、不同学科之间进行比较。研究发现,在排除国内同行的自引后,我国国际论文的真实国际影响力仍然有限,除了临床医学和物理等少数学科外,其他学科仍然低于全球平均水平。 相似文献
4.
Paul Donner 《Journal of Informetrics》2018,12(1):330-343
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. 相似文献
5.
Dalibor Fiala 《Journal of Informetrics》2012,6(3):370-388
In the past, recursive algorithms, such as PageRank originally conceived for the Web, have been successfully used to rank nodes in the citation networks of papers, authors, or journals. They have proved to determine prestige and not popularity, unlike citation counts. However, bibliographic networks, in contrast to the Web, have some specific features that enable the assigning of different weights to citations, thus adding more information to the process of finding prominence. For example, a citation between two authors may be weighed according to whether and when those two authors collaborated with each other, which is information that can be found in the co-authorship network. In this study, we define a couple of PageRank modifications that weigh citations between authors differently based on the information from the co-authorship graph. In addition, we put emphasis on the time of publications and citations. We test our algorithms on the Web of Science data of computer science journal articles and determine the most prominent computer scientists in the 10-year period of 1996–2005. Besides a correlation analysis, we also compare our rankings to the lists of ACM A. M. Turing Award and ACM SIGMOD E. F. Codd Innovations Award winners and find the new time-aware methods to outperform standard PageRank and its time-unaware weighted variants. 相似文献
6.
《Journal of Informetrics》2014,8(1):136-146
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. 相似文献
7.
《Journal of Informetrics》2020,14(2):101019
The normalized citation indicator may not be sufficiently reliable when a short citation time window is used, because the citation counts for recently published papers are not as reliable as those for papers published many years ago. In a limited time period, recent publications usually have insufficient time to accumulate citations and the citation counts of these publications are not sufficiently reliable to be used in the citation impact indicators. However, normalization methods themselves cannot solve this problem. To solve this problem, we introduce a weighting factor to the commonly used normalization indicator Category Normalized Citation Impact (CNCI) at the paper level. The weighting factor, which is calculated as the correlation coefficient between citation counts of papers in the given short citation window and those in the fixed long citation window, reflects the degree of reliability of the CNCI value of one paper. To verify the effect of the proposed weighted CNCI indicator, we compared the CNCI score and CNCI ranking of 500 universities before and after introducing the weighting factor. The results showed that although there was a strong positive correlation before and after the introduction of the weighting factor, some universities’ performance and rankings changed dramatically. 相似文献
8.
抽取2005—2006年中山大学公共卫生学院硕士研究生的学位论文共202篇,以其中的148篇MPH学位论文为研究组,54篇公共卫生全日制研究生学位论文为对照组,比较分析了两组学位论文引文规律及信息需求的差异。结果表明,MPH组的引文量及外文文献的引用率均低于全日制组,且引文率及外文文献引用率存在学科间差异;两组引文类型基本一致,但各类引文所占比例不同,普赖斯指数和半衰期也存在差异。建议通过多种方式提高MPH研究生的信息检索技巧、文献吸收能力。 相似文献
9.
In this paper we present a first large-scale analysis of the relationship between Mendeley readership and citation counts with particular documents’ bibliographic characteristics. A data set of 1.3 million publications from different fields published in journals covered by the Web of Science (WoS) has been analyzed. This work reveals that document types that are often excluded from citation analysis due to their lower citation values, like editorial materials, letters, news items, or meeting abstracts, are strongly covered and saved in Mendeley, suggesting that Mendeley readership can reliably inform the analysis of these document types. Findings show that collaborative papers are frequently saved in Mendeley, which is similar to what is observed for citations. The relationship between readership and the length of titles and number of pages, however, is weaker than for the same relationship observed for citations. The analysis of different disciplines also points to different patterns in the relationship between several document characteristics, readership, and citation counts. Overall, results highlight that although disciplinary differences exist, readership counts are related to similar bibliographic characteristics as those related to citation counts, reinforcing the idea that Mendeley readership and citations capture a similar concept of impact, although they cannot be considered as equivalent indicators. 相似文献
10.
11.
《Journal of Informetrics》2020,14(2):101013
A citation is a well-established mechanism for connecting scientific artifacts. Citation networks are used by citation analysis for a variety of reasons, prominently to give credit to scientists’ work. However, because of current citation practices, scientists tend to cite only publications, leaving out other types of artifacts such as datasets. Datasets then do not get appropriate credit even though they are increasingly reused and experimented with. We develop a network flow measure, called DataRank, aimed at solving this gap. DataRank assigns a relative value to each node in the network based on how citations flow through the graph, differentiating publication and dataset flow rates. We evaluate the quality of DataRank by estimating its accuracy at predicting the usage of real datasets: web visits to GenBank and downloads of Figshare datasets. We show that DataRank is better at predicting this usage compared to alternatives while offering additional interpretable outcomes. We discuss improvements to citation behavior and algorithms to properly track and assign credit to datasets. 相似文献
12.
随着交叉科学研究在促进社会发展重大综合性问题解决方面的优势逐渐凸显,越来越多的国家对交叉科学研究给予高度的重视与支持,如何对交叉科学的研究成果进行有效的鉴定与评估也成为科技管理部门亟待解决的重要问题。本文在传统引文指标的基础上,引入PLoS官方平台的使用数据(html浏览、xml下载及pdf下载)作为补充,综合评价交叉科学研究成果的影响力情况。以2009-2013年发表在开源期刊PLoS Computational Biology的研究论文为例,研究结果表明:(1)学科交叉水平与论文影响力之间存在一定的正向关系,学科交叉水平高的论文,对应的使用数据与引用数据要明显高于学科交叉水平较低的论文;(2)论文的使用数据与引用数据相互促进,在引用数据达到峰值时,对应的使用数据也会随之出现一定的回升;(3)学科交叉程度对使用数据与引用数据之间的相关关系也有较为显著的影响。本文从使用数据和引用数据两个维度探索交叉科学研究成果的影响力,为当前交叉科学研究成果影响力的评价提供了新的借鉴与参考。 相似文献
13.
The outgrow index measures to which extent an article outgrows – in terms of citations – the references on which it is based. In this article, three types of time series of outgrow indices and one outgrow index matrix are introduced. Examples of these time series are given illustrating the newly introduced concepts. These time series expand the toolbox for citation analysis by focusing on a specific subnetwork of the global citation network. It is stated that citation analysis has three application areas: information retrieval, research evaluation and structural citation network studies. This contribution is explicitly placed among structural network studies. 相似文献
14.
Reliable methods for the assessment of research success are still in discussion. One method, which uses the likelihood of publishing very highly cited papers, has been validated in terms of Nobel prizes garnered. However, this method cannot be applied widely because it uses the fraction of publications in the upper tail of citation distribution that follows a power law, which includes a low number of publications in most countries and institutions. To achieve the same purpose without restrictions, we have developed the double rank analysis, in which publications that have a low number of citations are also included. By ranking publications by their number of citations from highest to lowest, publications from institutions or countries have two ranking numbers: one for their internal and another one for world positions; the internal ranking number can be expressed as a function of the world ranking number. In log–log double rank plots, a large number of publications fit a straight line; extrapolation allows estimating the likelihood of publishing the highest cited publication. The straight line derives from a power law behavior of the double rank that occurs because citations follow lognormal distributions with values of μ and σ that vary within narrow limits. 相似文献
15.
Jane Stephens David E. Hubbard Carmelita Pickett Rusty Kimball 《The Journal of Academic Librarianship》2013
Citation analyses provide valuable insights into the usage of library collections and assist in collection management decision-making; however, there are few engineering citation analyses of faculty publications. This study addresses that gap through an analysis of 3488 citations from aerospace engineering faculty publications by source, format, age, and subject. Local holdings were assessed based on the 80/20 rule and journal titles ranked. In addition to supporting citation patterns identified in previous citation analyses, this study revealed some novel relationships involving formats and subjects. The results of this study have implications for collection management. 相似文献
16.
结合英文论文标题的已有研究成果,深入中文论文标题的探讨,通过数据统计定量分析中文论文标题类型的下载和引用的特点,以及标题长度和带冒号的标题对下载和引用的影响,揭示论文标题与下载和引用的关系,填补了国内关于这一研究的空白。 相似文献
17.
《Journal of Informetrics》2022,16(4):101350
This study explores the impact of different collaboration modes on the cited frequency of publications. Though several studies have obtained some research results, most of them exploit association or regression-based methods, which may not lead to causal conclusions. To overcome the above challenges, we use the Propensity Score Matching (PSM) method to analyze and compare the citation frequencies resulting from four groups of collaboration models: international versus domestic, international multilateral versus international bilateral, domestic inter-organizational versus domestic intra-organizational, and domestic multi-author versus domestic single-author. More specifically, we conduct this analysis by exploring the publications with three computer science subfields from the Web of Science (WoS) database. The experimental results show that international collaboration, especially international multilateral collaboration, has a significant role in increasing the frequency of citations to scientific publications, showing that internationalization and collaboration are critical factors in the growth of the impact of the papers. Among national co-publications, collaborative publications within national organizations receive a higher citation impact. Multi-author collaborations significantly increase citation frequency compared to single-author publications. Our heterogeneity analysis across the different subfields of the computer science domain finds that the treatment effects for the three subfields differ modestly and mostly significant from the whole sample. Moreover, besides the implications for developing research policy and scientist collaboration, our study can capture the causal effect between author collaboration patterns and citation frequency to reveal their causal effects. 相似文献
18.
We address issues concerning what one may learn from how citation instances are distributed in scientific articles. We visualize and analyze patterns of citation distributions in the full text of 350 articles published in the Journal of Informetrics. In particular, we visualize and analyze the distributions of citations in articles that are organized in a commonly seen four-section structure, namely, introduction, method, results, and conclusions (IMRC). We examine the locations of citations to the groundbreaking h-index paper by Hirsch in 2005 and how patterns associated with citation locations evolve over time. The results show that citations are highly concentrated in the first section of an article. The density of citations in the first section is about three times higher than that in subsequent sections. The distributions of citations to highly cited papers are even more uneven. 相似文献
19.
Forward citations of patents have been used extensively to capture the impact of technological knowledge. However, our understanding of the factors shaping patent citation patterns remains limited. One of the main limitations is the lack of scholarly attention paid to the dynamic influences arising from the evolution of technology fields. From an evolutionary perspective, technological impact is not simply determined by the static attributes of a technology itself; it is also dynamically affected by changes in the external conditions. Drawing on this viewpoint, this study suggests a model for understanding patent citation patterns by reflecting the evolution of the technology fields to which each patent belongs. Four such factors are explored: technology cycle time, potential of technological convergence, popularity of the technology field, and technological novelty. Based on the proposed model, we show how expected citation patterns can change as a result of different scenarios for technology field evolution. We conduct a case study of patents in the information technology and healthcare industries to show citation patterns of patents across heterogeneous industries as well as those within an industry. Contributions to the innovation literature and research investment decisions are discussed. 相似文献
20.
《Journal of Informetrics》2020,14(4):101080
It is widely accepted that data is fundamental for research and should therefore be cited as textual scientific publications. However, issues like data citation, handling and counting the credit generated by such citations, remain open research questions.Data credit is a new measure of value built on top of data citation, which enables us to annotate data with a value, representing its importance. Data credit can be considered as a new tool that, together with traditional citations, helps to recognize the value of data and its creators in a world that is ever more depending on data.In this paper we define data credit distribution (DCD) as a process by which credit generated by citations is given to the single elements of a database. We focus on a scenario where a paper cites data from a database obtained by issuing a query. The citation generates credit which is then divided among the database entities responsible for generating the query output. One key aspect of our work is to credit not only the explicitly cited entities, but even those that contribute to their existence, but which are not accounted in the query output.We propose a data credit distribution strategy (CDS) based on data provenance and implement a system that uses the information provided by data citations to distribute the credit in a relational database accordingly.As use case and for evaluation purposes, we adopt the IUPHAR/BPS Guide to Pharmacology (GtoPdb), a curated relational database. We show how credit can be used to highlight areas of the database that are frequently used. Moreover, we also underline how credit rewards data and authors based on their research impact, and not merely on the number of citations. This can lead to designing new bibliometrics for data citations. 相似文献