210,769 research outputs found
World citation and collaboration networks: uncovering the role of geography in science
Modern information and communication technologies, especially the Internet,
have diminished the role of spatial distances and territorial boundaries on the
access and transmissibility of information. This has enabled scientists for
closer collaboration and internationalization. Nevertheless, geography remains
an important factor affecting the dynamics of science. Here we present a
systematic analysis of citation and collaboration networks between cities and
countries, by assigning papers to the geographic locations of their authors'
affiliations. The citation flows as well as the collaboration strengths between
cities decrease with the distance between them and follow gravity laws. In
addition, the total research impact of a country grows linearly with the amount
of national funding for research & development. However, the average impact
reveals a peculiar threshold effect: the scientific output of a country may
reach an impact larger than the world average only if the country invests more
than about 100,000 USD per researcher annually.Comment: Published version. 9 pages, 5 figures + Appendix, The world citation
and collaboration networks at both city and country level are available at
http://becs.aalto.fi/~rajkp/datasets.htm
Assessing impact and quality from local dynamics of citation networks
International audienceWe show that essentially local dynamics of citation networks bring special information about the relevance/quality of a paper. Up to some rescaling, they exhibit universal behavior in citation dynamics: temporal patterns are remarkably consistent across disciplines, and uncover a prediction method for citations based on the structure of references only, at publication time. Above-average cited papers universally focus extensively on their own recent subfield - as such, citation counts essentially select what may plausibly be considered as the most disciplinary and normal science; whereas papers which have a peculiar dynamics, such as re-birthing scientific works - 'rediscovered classics' or 'early birds' - are comparatively poorly cited, despite their plausible relevance for the underlying communities. The "rebirth index" that we propose to quantify this phenomenon may be used as a complementary quality-defining criterion, in addition to final citation counts
Characterizing and modeling citation dynamics
Citation distributions are crucial for the analysis and modeling of the
activity of scientists. We investigated bibliometric data of papers published
in journals of the American Physical Society, searching for the type of
function which best describes the observed citation distributions. We used the
goodness of fit with Kolmogorov-Smirnov statistics for three classes of
functions: log-normal, simple power law and shifted power law. The shifted
power law turns out to be the most reliable hypothesis for all citation
networks we derived, which correspond to different time spans. We find that
citation dynamics is characterized by bursts, usually occurring within a few
years since publication of a paper, and the burst size spans several orders of
magnitude. We also investigated the microscopic mechanisms for the evolution of
citation networks, by proposing a linear preferential attachment with time
dependent initial attractiveness. The model successfully reproduces the
empirical citation distributions and accounts for the presence of citation
bursts as well.Comment: 8 pages, 5 figure
The Structure and Dynamics of Co-Citation Clusters: A Multiple-Perspective Co-Citation Analysis
A multiple-perspective co-citation analysis method is introduced for
characterizing and interpreting the structure and dynamics of co-citation
clusters. The method facilitates analytic and sense making tasks by integrating
network visualization, spectral clustering, automatic cluster labeling, and
text summarization. Co-citation networks are decomposed into co-citation
clusters. The interpretation of these clusters is augmented by automatic
cluster labeling and summarization. The method focuses on the interrelations
between a co-citation cluster's members and their citers. The generic method is
applied to a three-part analysis of the field of Information Science as defined
by 12 journals published between 1996 and 2008: 1) a comparative author
co-citation analysis (ACA), 2) a progressive ACA of a time series of
co-citation networks, and 3) a progressive document co-citation analysis (DCA).
Results show that the multiple-perspective method increases the
interpretability and accountability of both ACA and DCA networks.Comment: 33 pages, 11 figures, 10 tables. To appear in the Journal of the
American Society for Information Science and Technolog
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