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1.
采用模糊聚类分析方法对科技期刊综合学术影响力的分类进行研究。选取总被引频次、影响因子、即年指标、他引总引比、引用刊数、扩散因子和被引半衰期等7个期刊引证指标作为特征指标,以20种核科技期刊为分类对象,采用相关系数法建立模糊相似矩阵,进而对样本的聚类状态进行动态分析。分析结果显示,在λ=0．912水平下,20种核科技期刊聚为综合学术影响力明显不同的5类。同时,利用这一聚类结果,对某一核科技期刊的综合学术影响力作出了预报。 相似文献
2.
科技期刊学术影响力的动态评估模型 总被引：50，自引：12，他引：38
通过期刊评价的评估年限、期刊的来源文献量、影响因子和总被引频次等影响因素的分析,建立了科技期刊学术影响力的动态评估模型.评估计算实例表明,评估结果能够全面、客观、动态地反映科技期刊的学术影响力. 相似文献
3.
科技期刊部分评价指标的评估作用分析 总被引：19，自引：4，他引：15
采用平面直角坐标系找出产出力和影响力等几个重要指标之间的关系,认为影响因子是相对数,单纯讲影响因子越大,期刊学术影响力就越大是欠全面的.科技期刊应努力提高被引频次和他引率. 相似文献
4.
以2008—2010年三年的《中国科技期刊引证报告(核心版)》中影响因子、总被引频次、即年指标、他引率、基金论文比和载文量共6项指标为依据,赋于各项指标不同的权重并作归一化处理,综合评价2007—2009年12种儿科医学类核心期刊的学术影响力。《中华儿科杂志》的学术影响力综合指标始终排名第一,同时《实用儿科临床杂志》、《中国实用儿科杂志》和《临床儿科杂志》在同类期刊中也显示了较强的学术影响力。采用多指标数据归一化加权法评价学术期刊的学术影响力更加全面、公正、准确,可作为期刊评优、分级的有效方法。 相似文献
5.
基于2003-2007年Thomson Reuters和中国科学技术信息研究所历年发布的Journal Citation Reports(JCR)及<中国科技期刊引证报告>(CJCR),比较分析中外科技期刊载文数、总被引频次、影响因子、即年指标、被引半衰期等各项文献计量指标的变化趋势.结果显示,国内外科技期刊的平均载文量和总体学术影响力近年来一直在稳步上升,并且我国科技期刊近年来的发展速度要高于世界总体水平. 相似文献
6.
一位院士的情怀对科技期刊编辑的启示——阅读《大家博友》《大师小文》的感悟 总被引：1，自引：0，他引：1
针对学术期刊数字化程度与影响力提升的效应问题,重点对江苏省17种中文地学类期刊的网络化建设及应用程度做了调研和量化分析,并将其数据与统计期刊近5年的影响因子和被引频次做了分析比较.结果显示,被统计期刊学术影响力指标的上升趋势,与评价期刊数字化应用程度高低的得分值有很好的对应关系.进一步分析结果表明,代表期刊数字化程度较高的微信运用,有可能对提升科技期刊学术影响力起到意想不到的推动作用. 相似文献
7.
利用文献计量指标提高科技期刊质量 总被引：2，自引：0，他引：2
0引言衡量科技期刊学术、业务水平的标准有多种,包括载文量、文摘率、流通率(借阅率)、引文率、专家评审等。将这些标准量化为文献计量指标[1],借助文献计量学的统计数据可以使编辑部能够快速地对自己所办的科技期刊进行综合评价,了解期刊在本学科中所处的地位,及时调整编辑和出版策略。1被引指标与被引情况相关的文献计量指标有:总被引频次、Web即年下载率、影响因子(IF)、即年指标、他引率、自引率、被引半衰期、h指数。这些指标的统计数据均针对期刊影响力和期刊学术水平进行评估,反映了期刊的有用性(被利用程度)和显示度。总被引频次… 相似文献
8.
高被引论文是科技期刊学术影响力建立的基石,反映了期刊聚焦前沿热点,受读者关注度高,学术影响力大。本研究分析了综合性农业科学类中文核心期刊发表的高被引论文的期刊分布、发表年限和次数分布、作者所属机构和专业学科领域特征,结果表明：2011-2020年,31种综合性农业科学类核心期刊共发表了217篇被引频次超过100次的高被引论文。其中,《中国农业科学》发表的高被引论文数量最多,期刊影响力最大。各大学学报、各省农业科学和农业学报发表的高被引论文作者所属机构多数为期刊主办单位,或与期刊主办单位处于同一行政区域的单位;在综合性农业科学期刊中,农学、园艺和植物保护方向的高被引论文数量较多。基于此,提出综合性农业科学期刊编辑在选题策划和组稿时,可根据以上特征调整工作重心,旨在助力高影响力论文的产出和期刊影响力的提升。 相似文献
9.
10.
从编辑的视点探讨科技期刊Altmetrics的重要性 总被引：1，自引：0，他引：1
单篇学术论文客观的定量指标评价越来越受到重视,Altmetrics有别于传统文献计量评价中的被引频次指标,是一种采用评价网络上学术论文影响力的非传统的新计量方法。文章从编辑的视点分析归纳了Altmetrics所具有的客观性,公正、透明性,覆盖、社会性,补充性,实时性特征。通过文献研究、整理,得到在社交媒体中Altmetrics即时测量出的学术论文的影响力,与科技期刊的学术影响力相吻合;在开放存取领域中,Altmetrics学术影响力计量方法已得到认识、关注和应用,并为科技期刊的影响力计量化、可视化评价提供依据。 相似文献
11.
The journal impact factor (JIF) has been questioned considerably during its development in the past half-century because of its inconsistency with scholarly reputation evaluations of scientific journals. This paper proposes a publication delay adjusted impact factor (PDAIF) which takes publication delay into consideration to reduce the negative effect on the quality of the impact factor determination. Based on citation data collected from Journal Citation Reports and publication delay data extracted from the journals’ official websites, the PDAIFs for journals from business-related disciplines are calculated. The results show that PDAIF values are, on average, more than 50% higher than JIF results. Furthermore, journal ranking based on PDAIF shows very high consistency with reputation-based journal rankings. Moreover, based on a case study of journals published by ELSEVIER and INFORMS, we find that PDAIF will bring a greater impact factor increase for journals with longer publication delay because of reducing that negative influence. Finally, insightful and practical suggestions to shorten the publication delay are provided. 相似文献
12.
The journal impact factor (JIF) is the average of the number of citations of the papers published in a journal, calculated according to a specific formula; it is extensively used for the evaluation of research and researchers. The method assumes that all papers in a journal have the same scientific merit, which is measured by the JIF of the publishing journal. This implies that the number of citations measures scientific merits but the JIF does not evaluate each individual paper by its own number of citations. Therefore, in the comparative evaluation of two papers, the use of the JIF implies a risk of failure, which occurs when a paper in the journal with the lower JIF is compared to another with fewer citations in the journal with the higher JIF. To quantify this risk of failure, this study calculates the failure probabilities, taking advantage of the lognormal distribution of citations. In two journals whose JIFs are ten-fold different, the failure probability is low. However, in most cases when two papers are compared, the JIFs of the journals are not so different. Then, the failure probability can be close to 0.5, which is equivalent to evaluating by coin flipping. 相似文献
13.
以2012年JCR收录的数学期刊为例,采用偏度、峰度、JB检验、极大极小值比、离散系数、中位数均值比分析期刊评价指标的数据分布特点,并首次采用基尼系数分析期刊评价指标的内部差距,发现期刊评价指标普遍是右偏的,并且不服从正态分布;总被引频次、特征因子、即年指标的内部差距较大。期刊评价指标数据偏倚情况从好到坏的次序为:影响因子与5年影响因子>被引半衰期>论文影响分值>即年指标>特征因子>总被引频次。得出结论:指标数据偏倚会影响评价指标的数据标准化;指标数据偏倚会影响期刊一般水平的判断;指标数据右偏会导致期刊评价值偏低;最好选取数据偏倚情况相对较好的指标来评价期刊平均水平;数据偏倚对基于传统回归的计量研究影响较大。该结论有待进一步检验。 相似文献
14.
《Journal of Informetrics》2007,1(3):185-192
In this paper, we propose two methods for scoring scientific output based on statistical quantile plotting. First, a rescaling of journal impact factors for scoring scientific output on a macro level is proposed. It is based on normal quantile plotting which allows to transform impact data over several subject categories to a standardized distribution. This can be used in comparing scientific output of larger entities such as departments working in quite different areas of research. Next, as an alternative to the Hirsch index [Hirsch, J.E. (2005). An index to quantify an individuals scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569–16572], the extreme value index is proposed as an indicator for assessment of the research performance of individual scientists. In case of Lotkaian–Zipf–Pareto behaviour of citation counts of an individual, the extreme value index can be interpreted as the slope in a Pareto–Zipf quantile plot. This index, in contrast to the Hirsch index, is not influenced by the number of publications but stresses the decay of the statistical tail of citation counts. It appears to be much less sensitive to the science field than the Hirsch index. 相似文献
15.
本文为解决领域科技文献与专题价值的割裂问题提出深度融合科技文献、科研活动等科研对象与领域专题数据资源的图谱构建方法。通过主题词关联设计,构建包含期刊论文、期刊、科研机构、科研人员及专题实体类型的科研本体,选取机器学习专题构建科研知识图谱,并基于图数据库Neo4J进行图谱管理与查询验证。该专题科研知识图谱可以支持单实体/属性、多实体事实性问题的复杂图谱查询,有效揭示专题、科技文献的关联关系,具有较强的应用价值,可以为面向文献数据的智能知识服务提供新的思路和方向。 相似文献
16.
Sergio Copiello 《Learned Publishing》2019,32(3):249-258
This paper takes the cue from the case of a retracted paper, cited both by the retraction notice and by an article published later in the same journal. This led to analysis and discussion on the skewness of citations in the journal Sustainability and within Multidisciplinary Digital Publishing Institute (MDPI) journals, particularly investigating self‐citations at journal and publisher levels. I analysed articles published by Sustainability in 2015 and found that self‐citations are higher than expected under a uniform probability distribution. Self‐citations in this journal make a 36% difference to the journal's impact factor. This research raises the question of what citation patterns can be expected as normal, and where the boundary between normal and anomaly lies. I suggest the issue deserves further investigation because self‐citations have several implications, ranging from impact factors to visibility and influence of scientific journals. 相似文献
17.
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. 相似文献
18.
Document clustering of scientific texts using citation contexts 总被引：3，自引：0，他引：3
Document clustering has many important applications in the area of data mining and information retrieval. Many existing document
clustering techniques use the “bag-of-words” model to represent the content of a document. However, this representation is
only effective for grouping related documents when these documents share a large proportion of lexically equivalent terms.
In other words, instances of synonymy between related documents are ignored, which can reduce the effectiveness of applications
using a standard full-text document representation. To address this problem, we present a new approach for clustering scientific
documents, based on the utilization of citation contexts. A citation context is essentially the text surrounding the reference
markers used to refer to other scientific works. We hypothesize that citation contexts will provide relevant synonymous and
related vocabulary which will help increase the effectiveness of the bag-of-words representation. In this paper, we investigate
the power of these citation-specific word features, and compare them with the original document’s textual representation in
a document clustering task on two collections of labeled scientific journal papers from two distinct domains: High Energy
Physics and Genomics. We also compare these text-based clustering techniques with a link-based clustering algorithm which
determines the similarity between documents based on the number of co-citations, that is in-links represented by citing documents
and out-links represented by cited documents. Our experimental results indicate that the use of citation contexts, when combined
with the vocabulary in the full-text of the document, is a promising alternative means of capturing critical topics covered
by journal articles. More specifically, this document representation strategy when used by the clustering algorithm investigated
in this paper, outperforms both the full-text clustering approach and the link-based clustering technique on both scientific
journal datasets. 相似文献
19.
Konstantinos Petridis Chrisovalantis Malesios Garyfallos Arabatzis Emmanuel Thanassoulis 《Journal of Informetrics》2013,7(2):505-521
In this paper we attempt to assess the impact of journals in the field of forestry, in terms of bibliometric data, by providing an evaluation of forestry journals based on data envelopment analysis (DEA). In addition, based on the results of the conducted analysis, we provide suggestions for improving the impact of the journals in terms of widely accepted measures of journal citation impact, such as the journal impact factor (IF) and the journal h-index. More specifically, by modifying certain inputs associated with the productivity of forestry journals, we have illustrated how this method could be utilized to raise their efficiency, which in terms of research impact can then be translated into an increase of their bibliometric indices, such as the h-index, IF or eigenfactor score. 相似文献
20.
O. V. Fedorets 《Scientific and Technical Information Processing》2011,38(3):166-172
The standard impact factor allows one to compare scientific journals only within particular scientific subjects. To overcome
this limitation, another indicator of citation, viz., the thematically weighted impact factor (TWIF), is proposed. This indicator
allows one to compare journals of various subjects and takes the fact that a journal belongs to several subjects into account.
Information on the thematic headings of a journal and the value of a standard impact factor is necessary for calculation of
the indicator. The TWIF, which is calculated according to the citation index of Journal Citation Reports, is investigated in this article. 相似文献