Étiquette : Bibliometrics

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Beyond citations Scholars’ visibility on the social Web…

Beyond citations: Scholars’ visibility on the social Web :

“Traditionally, scholarly impact and visibility have been measured by counting publications and citations in the scholarly literature. However, increasingly scholars are also visible on the Web, establishing presences in a growing variety of social ecosystems. But how wide and established is this presence, and how do measures of social Web impact relate to their more traditional counterparts? To answer this, we sampled 57 presenters from the 2010 Leiden STI Conference, gathering publication and citations counts as well as data from the presenters’ Web “footprints.” We found Web presence widespread and diverse: 84% of scholars had homepages, 70% were on LinkedIn, 23% had public Google Scholar profiles, and 16% were on Twitter. For sampled scholars’ publications, social reference manager bookmarks were compared to Scopus and Web of Science citations; we found that Mendeley covers more than 80% of sampled articles, and that Mendeley bookmarks are significantly correlated (r=.45) to Scopus citation counts.”

URL : http://arxiv.org/abs/1205.5611

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Le classement de Leiden environnement scientifique et configuration…

Le classement de Leiden: environnement scientifique et configuration :

“Le classement de Leiden s’impose aujourd’hui comme une alternative pertinente et valable vis-à-vis de celui de Shanghai. De nombreux indicateurs font intervenir les caractéristiques propres aux champs disciplinaires et des calculs fondés sur le principe de distribution. Il est conçu par le centre CWTS de l’université néerlandaise de Leiden.”

“The Leiden Ranking is considered today as quite a pertinent and valuable alternative vs. the Shanghai Ranking. A significant number of indicators involve for instance Fields Citation Scores and data distribution. It is conceived by the CWTS of the University of Leiden – The Netherlands.”

URL : http://archivesic.ccsd.cnrs.fr/sic_00696098

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Bibliometric methods for detecting and analysing emerging research topics

This study gives an overview of the process of clustering scientific disciplines using hybrid methods, detecting and labelling emerging topics and analysing the results using bibliometrics methods.

The hybrid clustering techniques are based on biblographic coupling and text-mining and ‘core documents’, and cross-citation links are used to identify emerging fields.

The collaboration network of those countries that proved to be most active in the underlying disciplines, in combination with a set of standard indicators, form the groundwork for the bibliometric analysis of the detected emerging research topics.

URL : http://hdl.handle.net/10760/16947

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Trends in Research Librarianship Literature A Social Network…

Trends in Research Librarianship Literature: A Social Network Analysis of Articles :

“The purpose of this article is to identify the bibliometric characteristics of research librarianship literature and to visualize relationships in research librarianship by means of social network analysis. It was found out that the majority (66%) of the articles had single authorship and College & Research Libraries is the prominent actor among the research librarianship journals. It was also observed that Peter Hernon is the most productive and cited author in the field. The findings of this study can be used by the research librarianship community to better understand their core literature.”

URL : http://liber.library.uu.nl/publish/issues/2011-3_4/index.html?000554

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Which alternative tools for bibliometrics in an research…

Which alternative tools for bibliometrics in an research institute ? :

“Nowadays, bibliometrics is a frequently used tool in scientific and technical information, it can be useful to quantify scientific production and for collective or individual evaluations. Web of Science (Thomson ISI) and impact factor calculated by JCR are the better known references. We will underline the limits and setbacks of these overused indicators, especially the bias factor h. Other alternative tools are emerging today. Our presentation will focus on comparing all these products, and we will study their interests for librarians and researchers.”

“Aujourd’hui la bibliométrie est un outil fréquemment utilisé pour quantifier la production scientifique et aussi pour les évaluations des chercheurs et des institutions. Le WoK et le JCR pour le facteur d’impact sont des outils de référence. Nous voudrions souligner les limites de ces indicateurs, nous soulignerons les biais du facteur h. D’autres outils alternatifs émergent aujourd’hui. Cette communication analysera d’autres outils qui peuvent être utilisés en bibliométrie, nous en verrons les avantages et les inconvénients pour les documentalistes et les chercheurs.”

URL : http://archivesic.ccsd.cnrs.fr/sic_00668741

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Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact

Background

Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Web 2.0 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence. However, the relationship of the these new metrics to traditional metrics such as citations is not known.

Objective:

(1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles.

Methods

Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated.

Results

A total of 4208 tweets cited 286 distinct JMIR articles. The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 43.94% of all tweets in a 60-day period) or on the following day (528/3318, 15.9%), followed by a rapid decay. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from .42 to .72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. A linear multivariate model with time and tweets as significant predictors (P < .001) could explain 27% of the variation of citations. Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles (9/12 or 75% of highly tweeted article were highly cited, while only 3/43 or 7% of less-tweeted articles were highly cited; rate ratio 0.75/0.07 = 10.75, 95% confidence interval, 3.4–33.6). Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity.

Conclusions

Tweets can predict highly cited articles within the first 3 days of article publication. Social media activity either increases citations or reflects the underlying qualities of the article that also predict citations, but the true use of these metrics is to measure the distinct concept of social impact. Social impact measures based on tweets are proposed to complement traditional citation metrics. The proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time.

URL : http://www.jmir.org/2011/4/e123/

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Do age and professional rank influence the order of authorship in scientific publications? Some evidence from a micro-level perspective

Scientific authorship has important implications in science since it reflects the contribution to research of the different individual scientists and it is considered by evaluation committees in research assessment processes.

This study analyses the order of authorship in the scientific output of 1,064 permanent scientists at the Spanish CSIC (WoS, 1994–2004).

The influence of age, professional rank and bibliometric profile of scientists over the position of their names in the byline of publications is explored in three different research areas: Biology and Biomedicine, Materials Science and Natural Resources. There is a strong trend for signatures of younger researchers and those in the lower professional ranks to appear in the first position (junior signing pattern), while more veteran or highly-ranked ones, who tend to play supervisory functions in research, are proportionally more likely to sign in the last position (senior signing pattern).

Professional rank and age have an effect on authorship order in the three fields analysed, but there are inter-field differences. Authorship patterns are especially marked in the most collaboration-intensive field (i.e. Biology and Biomedicine), where professional rank seems to be more significant than age in determining the role of scientists in research as seen through their authorship patterns, while age has a more significant effect in the least collaboration-intensive field (Natural Resources).

URL : http://www.springerlink.com/content/e713j65334v77037/