Nonparametric methods for quantitative analysis (3rd ed.)
Nonparametric methods for quantitative analysis (3rd ed.)
Making large-scale support vector machine learning practical
Advances in kernel methods
Eye-tracking analysis of user behavior in WWW search
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A tutorial on support vector regression
Statistics and Computing
The bibliometric properties of article readership information: Research Articles
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Earlier Web usage statistics as predictors of later citation impact: Research Articles
Journal of the American Society for Information Science and Technology
The effect of “open access” on citation impact: An analysis of ArXiv's condensed matter section
Journal of the American Society for Information Science and Technology
The effect of use and access on citations
Information Processing and Management: an International Journal - Special issue: Infometrics
Egocentric analysis of co-authorship network structure, position and performance
Information Processing and Management: an International Journal
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arXiv.org mediates contact with the literature for entire scholarly communities, providing both archival access and daily email and web announcements of new materials. We confirm and extend a surprising correlation between article position in these initial announcements and later citation impact, due primarily to intentional “self-promotion” by authors. There is, however, also a pure “visibility” effect: the subset of articles accidentally in early positions fared measurably better in the long-term citation record. Articles in astrophysics (astro-ph) and two large subcommunities of theoretical high energy physics (hep-th and hep-ph) announced in position 1, for example, respectively received median numbers of citations 83%, 50%, and 100% higher than those lower down, while the subsets there accidentally had 44%, 38%, and 71% visibility boosts. We also consider the positional effects on early readership. The median numbers of early full text downloads for astro-ph, hep-th, and hep-ph articles announced in position 1 were 82%, 61%, and 58% higher than for lower positions, respectively, and those there accidentally had medians visibility-boosted by 53%, 44%, and 46%. Finally, we correlate a variety of readership features with long-term citations, using machine learning methods, and conclude with some observations on impact metrics and the dangers of recommender mechanisms. © 2009 Wiley Periodicals, Inc.