Research Article
Positional effects on citation and readership in arXiv
Article first published online: 22 JUL 2009
DOI: 10.1002/asi.21166
© 2009 ASIS&T
Issue

Journal of the American Society for Information Science and Technology
Volume 60, Issue 11, pages 2203–2218, November 2009
Additional Information
How to Cite
Haque, A.-u. and Ginsparg, P. (2009), Positional effects on citation and readership in arXiv. J. Am. Soc. Inf. Sci., 60: 2203–2218. doi: 10.1002/asi.21166
Publication History
- Issue published online: 6 OCT 2009
- Article first published online: 22 JUL 2009
- Manuscript Accepted: 1 JUN 2009
- Manuscript Revised: 29 MAY 2009
- Manuscript Received: 18 MAR 2009
- Abstract
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- Cited By
Abstract
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.

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