Scientometrics (SCIENTOMETRICS)

Publisher: Akadémiai Kiadó

Journal description

Scientometrics aims at publishing original studies short communications preliminary reports review papers letters to the editor and book reviews on scientometrics. The topics covered are results of research concerned with the quantitative features and characteristics of science. Emphasis is placed on investigations in which the development and mechanism of science are studied by means of (statistical) mathematical methods. The Journal also provides the reader with important up-to-date information about international meetings and events in scientometrics and related fields. Appropriate bibliographic compilations are published as a separate section. Due to its fully interdisciplinary character Scientometrics is indispensable to research workers and research administrators throughout the world. It provides valuable assistance to librarians and documentalists in central scientific agencies ministries research institutes and laboratories. Scientometrics includes the Journal of Research Communication Studies. Consequently its aims and scope cover that of the latter namely to bring the results of research investigations together in one place in such a form that they will be of use not only to the investigators themselves but also to the entrepreneurs and research workers who form the object of these studies.

Current impact factor: 2.18

Impact Factor Rankings

2016 Impact Factor Available summer 2017
2014 / 2015 Impact Factor 2.183
2013 Impact Factor 2.274
2012 Impact Factor 2.133
2011 Impact Factor 1.966
2010 Impact Factor 1.905
2009 Impact Factor 2.167
2008 Impact Factor 2.328
2007 Impact Factor 1.472
2006 Impact Factor 1.363
2005 Impact Factor 1.738
2004 Impact Factor 1.12
2003 Impact Factor 1.251
2002 Impact Factor 0.855
2001 Impact Factor 0.676
2000 Impact Factor 0.66
1999 Impact Factor 0.931
1998 Impact Factor 0.71
1997 Impact Factor 0.691
1996 Impact Factor 0.582
1995 Impact Factor 0.444
1994 Impact Factor 0.593
1993 Impact Factor 0.519
1992 Impact Factor 0.634

Impact factor over time

Impact factor

Additional details

5-year impact 2.32
Cited half-life 6.50
Immediacy index 0.33
Eigenfactor 0.01
Article influence 0.43
Website Scientometrics website
Other titles Scientometrics (Online)
ISSN 0138-9130
OCLC 45496762
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Akadémiai Kiadó

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Authors own final version only can be archived
    • Publisher's version/PDF cannot be used
    • On author's personal website or institutional repository or any repository mandated by Author's funding body
    • Published source must be acknowledged
    • Must state that the file is not the final published version of the paper
    • Must link to publisher version([DOI of the Article without brackets])
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification

Publications in this journal

  • Catherine P. Slade · Saundra J. Ribando · C. Kevin Fortner

    No preview · Article · Feb 2016 · Scientometrics
  • [Show abstract] [Hide abstract]
    ABSTRACT: Having combined data on Quebec scientists’ funding and journal publication, this paper tests the effect of holding a research chair on a scientist’s performance. The novelty of this paper is to use a matching technique to understand whether holding a research chair contributes to a better scientific performance. This method compares two different sets of regressions which are conducted on different data sets: one with all observations and another with only the observations of the matched scientists. Two chair and non-chair scientists are deemed matched with each other when they have the closest propensity score in terms of gender, research field, and amount of funding. The results show that holding a research chair is a significant scientific productivity determinant in the complete data set. However, when only matched scientists are kept in data set, holding a Canada research chair has a significant positive effect on scientific performance but other types of chairs do not have a significant effect. In the other words, in the case of two similar scientists in terms of gender, research funding, and research field, only holding a Canada research chair significantly affects scientific performance.
    No preview · Article · Feb 2016 · Scientometrics
  • [Show abstract] [Hide abstract]
    ABSTRACT: Citation index measures the impact or quality of a research publication. Currently, all the standard journal citation indices are used to measure the impact of individual research article published in those journals and are based on the citation count, making them a pure quantitative measure. To address this, as our first contribution, we propose to assign weights to the edges of citation network using three context based quality factors: 1. Sentiment analysis of the text surrounding the citation in the citing article, 2. Self-citations, 3. Semantic similarity between citing and cited article. Prior approaches make use of PageRank algorithm to compute the citation scores. This being an iterative process is not essential for acyclic citation networks. As our second contribution, we propose a non-iterative graph traversal based approach, which uses the edge weights and the initial scores of the non-cited nodes to compute the citation indices by visiting the nodes in topologically sorted order. Experimental results depict that rankings of citation indices obtained by our approach are improved over the traditional citation count based ranks. Also, our rankings are similar to that of PageRank based methods; but, our algorithm is simpler and 70 % more efficient. Lastly, we propose a new model for future reference, which computes the citation indices based on solution of system of linear inequalities, in which human-expert’s judgment is modeled by suitable linear constraints.
    No preview · Article · Feb 2016 · Scientometrics
  • [Show abstract] [Hide abstract]
    ABSTRACT: The research area of scientometrics began during the second half of the nineteenth century. After decades of growth, the international field of scientometrics has become increasingly mature. This study intends to understand the evolution of the collaboration network in the field of scientometrics. The growth of the discipline is divided into three stages: the first period (1987–1996), the second period (1997–2006), and the third period (2007–2015). Macro-level, meso-level, and micro-level network measures across the time periods are compared. Macro-level analyses show that the degree distribution of the collaboration in each time span are consistent with power-law, and that both the average degree and average distance steadily increase with time. From the meso-level perspective, the increase of the number of clusters in the collaboration networks suggests the emergence of more collaborative fields in scientometrics. Moreover, the growth of the size of primary clusters demonstrates the expansion of the research fields and the collaboration range. Micro-level structure analyses identify the authors/researchers with high performance in raw degree measure, degree centrality measure, and betweenness measure, all of which are dynamic across different time spans. From three dimensions (raw degree, degree centrality, and betweenness centrality), the collaboration dominators are identified for each time span.
    No preview · Article · Feb 2016 · Scientometrics
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper we investigate the problem of university classification and its relation to ranking practices in the policy context of an official evaluation of Romanian higher education institutions and their study programs. We first discuss the importance of research in the government-endorsed assessment process and analyze the evaluation methodology and the results it produced. Based on official documents and data we show that the Romanian classification of universities was implicitly hierarchical in its conception and therefore also produced hierarchical results due to its close association with the ranking of study programs and its heavy reliance on research outputs. Then, using a distinct dataset on the research performance of 1385 faculty members working in the fields of political science, sociology and marketing we further explore the differences between university categories. We find that our alternative assessment of research productivity—measured with the aid of Hirsch’s (Proc Natl Acad Sci 102(46):16569–16572, 2005) h-index and with Egghe’s (Scientometrics 69(1):131–152, 2006) g-index—only provides empirical support for a dichotomous classification of Romanian institutions.
    No preview · Article · Feb 2016 · Scientometrics

  • No preview · Article · Feb 2016 · Scientometrics

  • No preview · Article · Jan 2016 · Scientometrics

  • No preview · Article · Jan 2016 · Scientometrics