I think that many of you will find interesting such a question: which papers download best. Often researchers download articles without going into details of their contents, and start making a close study of the papers only after downloading them. From my experience, I can say that all else being equal, the articles that download best are the ones with mathematical models or the ones with catchy titles. What do you think about this? Has any one you happened to determine any relation between your own citation index and the number of downloads of their articles?
Dear Dr. Vladimir Moskovkin, In general a reader first look the area of the research paper. Then we look any interesting algorithm or software or our popular programming language is used.
Citation and download index has their relation probability from 0 to 1. But a download does not guarantees for citation.
It is known that ratio "reads" to "cites" will vary by fields. For example, Kurtz et al (2004) report it as 17:1 and even 12:1 in astrophysics. Odlyzko (2006) predicts analogous trend in mathematics. Tim Brody"s correlator / predictor - gives the size of the download / citation correlation by field, which can be used to predict citations 6 - 24 months later from downloads today (with an adjustable time-window). Correlator / Prediction: The correlator counts downloads and citations for an article within an adjustable "window of time' as well as adjustable value ranges for downloads and citations, and calculates their correlation. For example, it could calculate the correlation between downloads and citations within a two-year window for articles in the top quartile of downloads and the bottom quartile of citations. The windows and ranges can be made as wide or narrow as one wishes. The correlation can be as high as 0.4 - 0.6, which means that one can predict from today"s downloads what citations two years from now will look like.
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