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| == Summary == | | == Summary == |
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| |description = Fig. 3 of [[CZ:Ref:Neylon 2009 Article-Level Metrics and the Evolution of Scientific Impact]]. Figure legend: Article-level metrics provided by PLoS. Shown here are article-level metrics for a recent article in PLoS Comput Biol [[http://dx.doi.org/10.1371/journal.pcbi.1000037 13]], accessible by clicking the “Metrics” tab on the article Web page. At the top, page view and download counts provide an immediate measure of the number of times people accessed the article via the journal Web site. The plot showing cumulative views gives a sense of the trend in views over time. Citations are shown next and refer to the number of other articles that have referenced this one as indexed in citation databases; PubMed Central and Google Scholar in this case. Citations typically take months or years to appear, but are better indicators of how many other articles have built upon the work. “Other Indicators of Impact” include ratings and comments, which, like page views, are immediate but may offer more insight because users are more likely to have read the article and found it compelling enough to respond. Additional other indicators are bookmarks, used by some people to keep track of articles of interest to them, and blog posts and trackbacks, which indicate where else on the Web the article has been mentioned and can be useful for linking to a broader discussion. It is clear that all of the types of data provide different dimensions, which together can give a clearer picture of an article's impact.
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| |author = Cameron Neylon & Shirley Wu
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| |copyright = Cameron Neylon & Shirley Wu
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| |source = [http://dx.doi.org/10.1371/journal.pbio.1000242.g003 doi: 10.1371/journal.pbio.1000242.g003]
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| |date-created = Published November 17, 2009
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| |pub-country = United States
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| |notes =
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| |versions =
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| == Licensing/Copyright status ==
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| {{CC|by|2.5}}
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