共查询到20条相似文献，搜索用时 625 毫秒
1.
Dissertations can be the single most important scholarly outputs of junior researchers. Whilst sets of journal articles are often evaluated with the help of citation counts from the Web of Science or Scopus, these do not index dissertations and so their impact is hard to assess. In response, this article introduces a new multistage method to extract Google Scholar citation counts for large collections of dissertations from repositories indexed by Google. The method was used to extract Google Scholar citation counts for 77,884 American doctoral dissertations from 2013 to 2017 via ProQuest, with a precision of over 95%. Some ProQuest dissertations that were dual indexed with other repositories could not be retrieved with ProQuest-specific searches but could be found with Google Scholar searches of the other repositories. The Google Scholar citation counts were then compared with Mendeley reader counts, a known source of scholarly-like impact data. A fifth of the dissertations had at least one citation recorded in Google Scholar and slightly fewer had at least one Mendeley reader. Based on numerical comparisons, the Mendeley reader counts seem to be more useful for impact assessment purposes for dissertations that are less than two years old, whilst Google Scholar citations are more useful for older dissertations, especially in social sciences, arts and humanities. Google Scholar citation counts may reflect a more scholarly type of impact than that of Mendeley reader counts because dissertations attract a substantial minority of their citations from other dissertations. In summary, the new method now makes it possible for research funders, institutions and others to systematically evaluate the impact of dissertations, although additional Google Scholar queries for other online repositories are needed to ensure comprehensive coverage. 相似文献
2.
[目的/意义] 进一步探讨Web 2.0环境下选择性计量指标的有效性。[方法/过程] 以"data mining"为检索词,获得Mendeley与Web of Science两平台的交叉文献集合,分别对交叉文集的被引频数与阅读数、被引频数与标签数进行相关性检验后,从每组选取指标值差异最大与最小的各100篇文献进行具体分析。[结果/结论] 传统计量指标被引频数与Mendeley中的阅读数和标签数均存在弱相关性,证实了以阅读数和标签数为代表的选择性计量指标可以在一定程度上评估文献的影响力,且文献类型、出版年份和作者h指数会对用户阅读、引用等文献利用行为产生影响。未来文献影响力评价的发展方向应为传统文献计量方法与选择性计量方法的结合。 相似文献
3.
Altmetrics from Altmetric.com are widely used by publishers and researchers to give earlier evidence of attention than citation counts. This article assesses whether Altmetric.com scores are reliable early indicators of likely future impact and whether they may also reflect non-scholarly impacts. A preliminary factor analysis suggests that the main altmetric indicator of scholarly impact is Mendeley reader counts, with weaker news, informational and social network discussion/promotion dimensions in some fields. Based on a regression analysis of Altmetric.com data from November 2015 and Scopus citation counts from October 2017 for articles in 30 narrow fields, only Mendeley reader counts are consistent predictors of future citation impact. Most other Altmetric.com scores can help predict future impact in some fields. Overall, the results confirm that early Altmetric.com scores can predict later citation counts, although less well than journal impact factors, and the optimal strategy is to consider both Altmetric.com scores and journal impact factors. Altmetric.com scores can also reflect dimensions of non-scholarly impact in some fields. 相似文献
4.
Mike Thelwall 《Journal of Informetrics》2018,12(4):1031-1041
There are known gender imbalances in participation in scientific fields, from female dominance of nursing to male dominance of mathematics. It is not clear whether there is also a citation imbalance, with some claiming that male-authored research tends to be more cited. No previous study has assessed gender differences in the readers of academic research on a large scale, however. In response, this article assesses whether there are gender differences in the average citations and/or Mendeley readers of academic publications. Field normalised logged Scopus citations and Mendeley readers from mid-2018 for articles published in 2014 were investigated for articles with first authors from India, Spain, Turkey, the UK and the USA in up to 251 fields with at least 50 male and female authors. Although female-authored research is less cited in Turkey (?4.0%) and India (?3.6%), it is marginally more cited in Spain (0.4%), the UK (0.4%), and the USA (0.2%). Female-authored research has fewer Mendeley readers in India (?1.1%) but more in Spain (1.4%), Turkey (1.1%), the UK (2.7%) and the USA (3.0%). Thus, whilst there may be little practical gender difference in citation impact in countries with mature science systems, the higher female readership impact suggests a wider audience for female-authored research. The results also show that the conclusions from a gender analysis depend on the field normalisation method. A theoretically informed decision must therefore be made about which normalisation to use. The results also suggest that arithmetic mean-based field normalisation is favourable to males. 相似文献
5.
Hamid R. Jamali 《Library & information science research》2018,40(3-4):201-207
In spite of the increasing use of qualitative research methods in library and information studies, it is unclear whether using qualitative methods (grounded theory, ethnography, and phenomenology) results in an above average impact in library and information science (LIS). Articles using any of the three qualitative methods published from 2003 to 2013 and indexed in Web of Science in the category of “Information Science & Library Science” (N?=?299) were studied. The number of citations and Mendeley readers for each article was compared to the other articles published in the same journal and same volume using mean normalised rank (rank-1/articles-1). The results showed no statistically significant difference between the citation rates of qualitative articles with those of other articles. Qualitative articles on average had a smaller Mendeley readership than the other articles did and the difference was statistically significant. Given the increasing interest in qualitative methods, it is suggested that LIS schools in their education programs and journals in their editorial policies should put more emphasis on issues related to the rigour of qualitative research. 相似文献
6.
《Journal of Informetrics》2022,16(3):101318
References formulate the foundation and endorsements of scientific research. Using articles published in 2005 covered by Microsoft Academic Graph, the current paper defines and calculates five indicators of references, i.e., the number of references, the number of citations of references, the age of references, the number of nodes in a reference cascade (a multi-generation reference network), and the density of bibliographic coupling networks by references, and investigates their relations with the citation impact of the focal publication. A non-linear relationship is shown in all the five indicators; specifically, we observe two types of patterns, namely inverted-L and -U relations, both presenting the existence of critical points. We further explore the discipline-level differences of such a relationship and how it relates to the characteristics of the discipline itself. Among all five indicators, the effect of disciplinary academic “environments” is universally identified. We believe that the current paper provides insightful views to the discussion regarding the significance of a reference list. 相似文献
7.
[目的/意义]通过对Mendeley阅读数据的分析,探讨引用行为之外更广范围的论文使用行为,以进一步完善学术论文的影响力评价体系。[方法/过程]选择社会学、历史学、生态学和应用物理学四个学科领域,从Scopus、Altmetric.com采集被引数据和阅读数据,并进行相关性分析。从身份、国别以及学科三个角度对Mendeley阅读数据Top100的文献用户身份和行为特征进行深入的探究。[结果/结论]在四个学科文献集合中,Mendeley阅读数据均比被引频次的覆盖率高,说明引用行为只是论文使用的冰山一角。对于不同使用动机的用户,其使用行为都存在学科差异;不同国家使用者对论文的使用习惯有地域差异;学术论文的跨学科使用情况与自身学科特性密切相关。 相似文献
8.
The paper introduces a new journal impact measure called The Reference Return Ratio (3R). Unlike the traditional Journal Impact Factor (JIF), which is based on calculations of publications and citations, the new measure is based on calculations of bibliographic investments (references) and returns (citations). A comparative study of the two measures shows a strong relationship between the 3R and the JIF. Yet, the 3R appears to correct for citation habits, citation dynamics, and composition of document types – problems that typically are raised against the JIF. In addition, contrary to traditional impact measures, the 3R cannot be manipulated ad infinitum through journal self-citations. 相似文献
9.
[目的/意义] 比较分析不同学科的外文学术电子图书影响力差异,丰富电子图书评价方法,为完善电子图书分类分学科的科学评价体系提供有益参考。[方法/过程] 采用Bookmetrix,以经管类、教育类的学术电子图书为研究对象,对其传统引文指标与Altmetrics指标（Mendeley读者数、关注量、下载量）、书评量的相关性与一致性定量分析,比较两学科外文电子图书各指标之间的差异并进行非参数检验。[结果/结论] 研究发现：被引量、读者数、下载量等具有较高的指标覆盖率;经K-S Z独立双样本检验,经管类和教育类电子图书的被引量、下载量存在显著差异,关注量、读者数、书评量无显著差异（p=0.05）;指标相关性具有学科差异性,被引量与Mendeley读者数的相关性,经管类图书高于教育类图书;被引量测度的是学术电子图书的学术影响力,使用数据（下载量等）与补充计量学数据较多反映图书的社会影响力。评价中文学术电子图书应将多源异构数据处理转化,构建多指标综合评价体系,将定性与定量方法相融合,使评价更全面、科学。 相似文献
10.
11.
为了探讨同行评议、影响计量学以及传统文献计量指标在科学评价中的有效性,本文选取F1000、Mendeley以及Web of Science、Google Scholar数据库,采用SPSS 19.0软件,将心理学与生态学的1,3篇论文的同行评议结果即F1000因子、Mendeley阅读统计、期刊影响因子,以及Web of Science、Google Scholar数据库中被引频次进行相关分析。结果表明:同行评议结果、传统引文分析指标以及以Mendeley为代表的影响计量指标具有低度正相关性,这意味着上述指标在科学评价中审视视角的不同以及数字时代科学评价的多维构成;心理学筛选数据中F1000因子与期刊影响因子相关度几近为0,这一结论进一步证实了期刊影响因子与单篇论文影响力的严重背离;生态学与心理学指标相关分析结果的不同折射出科学评价中自然科学、社会科学的差异。图3。表4。参考文献10。 相似文献
12.
This paper presents an empirical analysis of two different methodologies for calculating national citation indicators: whole counts and fractionalised counts. The aim of our study is to investigate the effect on relative citation indicators when citations to documents are fractionalised among the authoring countries. We have performed two analyses: a time series analysis of one country and a cross-sectional analysis of 23 countries. The results show that all countries’ relative citation indicators are lower when fractionalised counting is used. Further, the difference between whole and fractionalised counts is generally greatest for the countries with the highest proportion of internationally co-authored articles. In our view there are strong arguments in favour of using fractionalised counts to calculate relative citation indexes at the national level, rather than using whole counts, which is the most common practice today. 相似文献
13.
In citation network analysis, complex behavior is reduced to a simple edge, namely, node A cites node B. The implicit assumption is that A is giving credit to, or acknowledging, B. It is also the case that the contributions of all citations are treated equally, even though some citations appear multiply in a text and others appear only once. In this study, we apply text-mining algorithms to a relatively large dataset (866 information science articles containing 32,496 bibliographic references) to demonstrate the differential contributions made by references. We (1) look at the placement of citations across the different sections of a journal article, and (2) identify highly cited works using two different counting methods (CountOne and CountX). We find that (1) the most highly cited works appear in the Introduction and Literature Review sections of citing papers, and (2) the citation rankings produced by CountOne and CountX differ. That is to say, counting the number of times a bibliographic reference is cited in a paper rather than treating all references the same no matter how many times they are invoked in the citing article reveals the differential contributions made by the cited works to the citing paper. 相似文献
14.
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
15.
林平 《大学图书情报学刊》2007,25(1):86-90
科学文献的相互引用关系是引文分析的主要依据.引文分析是以文献引用数据为基础,用以揭示其数量特征和规律的一种文献计量分析方法.作者对<大学图书情报学刊>1998年与2004年的引文数量进行了量化分析,指出了刊物在引文数量、引文文献类型、引文语种、引文主题、引文原始来源期刊的发展和变化情况,提出了值得重视的有关问题. 相似文献
16.
[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
17.
[目的/意义] 专利引文分析方法被广泛运用,但专利审查员引文的价值却常常被低估甚至误读,亟待澄清,这关乎专利文献内在机理的理解与专利文献潜在价值的挖掘。[方法/过程] 根据施引主体的不同,专利引文可分为申请人引文和审查员引文两类。比较表明,这两类引文有明显的区别特征。与申请人引文相比,专利审查员引文具有三大区别特征:一是施引专利与被引文献之间具有确定的技术相关性,二是格式规范、高度标准化,三是可获得性与数量优势明显。[结果/结论] 专利审查员引文的区别特征决定了其具有诉讼证据价值、知识交流和专利影响力的测量工具价值以及企业竞争情报价值。大数据技术的应用有助于专利审查员引文的价值实现,但其价值的深度挖掘还有待审查数据的充分公开、标引的规范和工具的优化。 相似文献
18.
Kevin W. Boyack Nees Jan van Eck Giovanni Colavizza Ludo Waltman 《Journal of Informetrics》2018,12(1):59-73
We report characteristics of in-text citations in over five million full text articles from two large databases – the PubMed Central Open Access subset and Elsevier journals – as functions of time, textual progression, and scientific field. The purpose of this study is to understand the characteristics of in-text citations in a detailed way prior to pursuing other studies focused on answering more substantive research questions. As such, we have analyzed in-text citations in several ways and report many findings here. Perhaps most significantly, we find that there are large field-level differences that are reflected in position within the text, citation interval (or reference age), and citation counts of references. In general, the fields of Biomedical and Health Sciences, Life and Earth Sciences, and Physical Sciences and Engineering have similar reference distributions, although they vary in their specifics. The two remaining fields, Mathematics and Computer Science and Social Science and Humanities, have different reference distributions from the other three fields and between themselves. We also show that in all fields the numbers of sentences, references, and in-text mentions per article have increased over time, and that there are field-level and temporal differences in the numbers of in-text mentions per reference. A final finding is that references mentioned only once tend to be much more highly cited than those mentioned multiple times. 相似文献
19.
[目的/意义]施引文献与被引文献往往存在着某种相似性,揭示这种现象背后的形成机制有助于深入理解引文的本质。[方法/过程]采用指数随机图模型,以图书馆与情报学领域为对象开展实证分析,旨在揭示文献相似性对引用关系的影响机制。[结果/结论]实证研究发现：在网络结构、机构、期刊层面存在显著的引用文献相似倾向。具体地,引用关系更倾向于嵌入三角传递结构;来源于相同机构和期刊的文献之间更容易产生引用关系;来源于学科优势地位国家的文献之间更容易产生引用。实证结果充分说明社会接近性是引用行为的重要形成机制,反映了引用偏好的社会属性。 相似文献
20.
The Citation Cloud of a biomedical article: a free,public, web-based tool enabling citation analysis
Neil R. Smalheiser Jodi Schneider Vetle I. Torvik Dean P. Fragnito Eric E. Tirk 《Journal of the Medical Library Association》2022,110(1):103
Background:An article''s citations are useful for finding related articles that may not be readily found by keyword searches or textual similarity. Citation analysis is also important for analyzing scientific innovation and the structure of the biomedical literature. We wanted to facilitate citation analysis for the broad community by providing a user-friendly interface for accessing and analyzing citation data for biomedical articles.Case Presentation:We seeded the Citation Cloud dataset with over 465 million open access citations culled from six different sources: PubMed Central, Microsoft Academic Graph, ArnetMiner, Semantic Scholar, Open Citations, and the NIH iCite dataset. We implemented a free, public extension to PubMed that allows any user to visualize and analyze the entire citation cloud around any paper of interest A: the set of articles cited by A, those which cite A, those which are co-cited with A, and those which are bibliographically coupled to A.Conclusions:Citation Cloud greatly enables the study of citations by the scientific community, including relatively advanced analyses (co-citations and bibliographic coupling) that cannot be undertaken using other available tools. The tool can be accessed by running any PubMed query on the Anne O''Tate value-added search interface and clicking on the Citations button next to any retrieved article. 相似文献