Life, Death and Preferential Attachment

Scientific communities are characterized by strong stratification. The highly skewed frequency distribution of citations of published scientific papers suggests a relatively small number of active, cited papers embedded in a sea of inactive and uncited papers. We propose an analytically soluble model which allows for the death of nodes. This model provides an excellent description of the citation distributions for live and dead papers in the SPIRES database. Further, this model suggests a novel and general mechanism for the generation of power law distributions in networks whenever the fraction of active nodes is small.Comment: 5 pages, 2 figure

Correlations in Networks associated to Preferential Growth

Combinations of random and preferential growth for both on-growing and stationary networks are studied and a hierarchical topology is observed. Thus for real world scale-free networks which do not exhibit hierarchical features preferential growth is probably not the main ingredient in the growth process. An example of such real world networks includes the protein-protein interaction network in yeast, which exhibits pronounced anti-hierarchical features.Comment: 4 pages, 4 figure

The Geography of Scientific Productivity: Scaling in U.S. Computer Science

Here we extract the geographical addresses of authors in the Citeseer database of computer science papers. We show that the productivity of research centres in the United States follows a power-law regime, apart from the most productive centres for which we do not have enough data to reach definite conclusions. To investigate the spatial distribution of computer science research centres in the United States, we compute the two-point correlation function of the spatial point process and show that the observed power-laws do not disappear even when we change the physical representation from geographical space to cartogram space. Our work suggests that the effect of physical location poses a challenge to ongoing efforts to develop realistic models of scientific productivity. We propose that the introduction of a fine scale geography may lead to more sophisticated indicators of scientific output.Comment: 6 pages, 3 figures; minor change

Runaway Events Dominate the Heavy Tail of Citation Distributions

Statistical distributions with heavy tails are ubiquitous in natural and social phenomena. Since the entries in heavy tail have disproportional significance, the knowledge of its exact shape is very important. Citations of scientific papers form one of the best-known heavy tail distributions. Even in this case there is a considerable debate whether citation distribution follows the log-normal or power-law fit. The goal of our study is to solve this debate by measuring citation distribution for a very large and homogeneous data. We measured citation distribution for 418,438 Physics papers published in 1980-1989 and cited by 2008. While the log-normal fit deviates too strong from the data, the discrete power-law function with the exponent $\gamma=3.15$ does better and fits 99.955% of the data. However, the extreme tail of the distribution deviates upward even from the power-law fit and exhibits a dramatic "runaway" behavior. The onset of the runaway regime is revealed macroscopically as the paper garners 1000-1500 citations, however the microscopic measurements of autocorrelation in citation rates are able to predict this behavior in advance.Comment: 6 pages, 5 Figure

Consensuality of Peer Nominations Among Scientists

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/69069/2/10.1177_107554708200400210.pd

Inheritance patterns in citation networks reveal scientific memes

Memes are the cultural equivalent of genes that spread across human culture by means of imitation. What makes a meme and what distinguishes it from other forms of information, however, is still poorly understood. Our analysis of memes in the scientific literature reveals that they are governed by a surprisingly simple relationship between frequency of occurrence and the degree to which they propagate along the citation graph. We propose a simple formalization of this pattern and we validate it with data from close to 50 million publication records from the Web of Science, PubMed Central, and the American Physical Society. Evaluations relying on human annotators, citation network randomizations, and comparisons with several alternative approaches confirm that our formula is accurate and effective, without a dependence on linguistic or ontological knowledge and without the application of arbitrary thresholds or filters.Comment: 8 two-column pages, 5 figures; accepted for publication in Physical Review

Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On

Community structure and patterns of scientific collaboration in Business and Management

This is the author's accepted version of this article deposited at arXiv (arXiv:1006.1788v2 [physics.soc-ph]) and subsequently published in Scientometrics October 2011, Volume 89, Issue 1, pp 381-396. The final publication is available at link.springer.com http://link.springer.com/article/10.1007%2Fs11192-011-0439-1Author's note: 17 pages. To appear in special edition of Scientometrics. Abstract on arXiv meta-data a shorter version of abstract on actual paper (both in journal and arXiv full pape

The Impact of Boundary Spanning Scholarly Publications and Patents

Human knowledge and innovation are recorded in two media: scholarly publication and patents. These records not only document a new scientific insight or new method developed, but they also carefully cite prior work upon which the innovation is built.We quantify the impact of information flow across fields using two large citation dataset: one spanning over a century of scholarly work in the natural sciences, social sciences and humanities, and second spanning a quarter century of United States patents.We find that a publication's citing across disciplines is tied to its subsequent impact. In the case of patents and natural science publications, those that are cited at least once are cited slightly more when they draw on research outside of their area. In contrast, in the social sciences, citing within one's own field tends to be positively correlated with impact

Is Medical Research Informing Professional Practice More Highly Cited? Evidence from AHFS DI Essentials in Drugs.com

This is an accepted manuscript of an article published by Springer in Scientometrics on 21/02/2017, available online: https://doi.org/10.1007/s11192-017-2292-3 The accepted version of the publication may differ from the final published version.Citation-based indicators are often used to help evaluate the impact of published medical studies, even though the research has the ultimate goal of improving human wellbeing. One direct way of influencing health outcomes is by guiding physicians and other medical professionals about which drugs to prescribe. A high profile source of this guidance is the AHFS DI Essentials product of the American Society of Health-System Pharmacists, which gives systematic information for drug prescribers. AHFS DI Essentials documents, which are also indexed by Drugs.com, include references to academic studies and the referenced work is therefore helping patients by guiding drug prescribing. This article extracts AHFS DI Essentials documents from Drugs.com and assesses whether articles referenced in these information sheets have their value recognised by higher Scopus citation counts. A comparison of mean log-transformed citation counts between articles that are and are not referenced in AHFS DI Essentials shows that AHFS DI Essentials references are more highly cited than average for the publishing journal. This suggests that medical research influencing drug prescribing is more cited than average