9. Introduction: Social Bookmarking in STM 1 Approximate number of estimated cookies on a site for April 2010 (Google, Inc., 2010) 2 Estimated number of times a site is accessed by unique visitors in April 2010 (Google, Inc., 2010). 3 Total estimated number of times pages on a site have been accessed by users (Google, Inc., 2010) CiteULike Connotea BibSonomy 2collab Launch 2004 2004 2006 2007 Responsibility Oversity Ltd. sponsored by Springer Nature Publishing Group University of Kassel Elsevier B.V. Unique visitors 1 360,000 380,000 350,000 40,000 Total visits 2 480,000 690,000 620,000 44,000 Page views 3 2,100,000 3,100,000 2,800,000 180,000
10. Introduction: Social Bookmarking in STM 1 Approximate number of estimated cookies on a site for April 2010 (Google, Inc., 2010) 2 Estimated number of times a site is accessed by unique visitors in April 2010 (Google, Inc., 2010). 3 Total estimated number of times pages on a site have been accessed by users (Google, Inc., 2010) CiteULike Connotea BibSonomy 2collab Launch 2004 2004 2006 2007 Responsibility Oversity Ltd. sponsored by Springer Nature Publishing Group University of Kassel Elsevier B.V. Unique visitors 1 360,000 380,000 350,000 40,000 Total visits 2 480,000 690,000 620,000 44,000 Page views 3 2,100,000 3,100,000 2,800,000 180,000
26. Journal Evaluation: Tags number of unique tags Number of tags per publication year for all bookmarked articles
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Editor's Notes
presentation is part of an ongoing research project about multidimensional journal evaltuation five dimensions test set Social bookmarking data is used to analyze two dimensions: journal content journal perception which is the readership or usage of scientific journals
analysis of readership is still problematic despite standards like Project Counter that try to measure usage by downloads of electronic articles above all, the usage statistics are not made available on a global scale but only on the level of one‘s own institute as an alternative, the analysis of data from social bookmarking services is introduced to measure worldwide journal usage bookmarking an article can be counted similar to counting downloads
social bookmarking platforms in STM are modeled on delicious, the social bookmarking service that allows you to store web bookmarks platforms specialized on science cater the specific needs of academic users and allow for bookmarking scientific literature since a resource is always connected with its user and the assigned tag, it is possible to find relevant content through other users and tags
this is how a scientific social bookmarking service works: if you have installed the so called bookmarklet, you can bookmark an article right from the publisher’s site
the metadata should be extracted and added to your library
if the bookmark was set successfully, you can also see who else already stored this paper and what other literature this user bookmarked and which tags he assigned
there are four social bookmarking services that provide the same service specialized on academics: CiteULike being the oldest, followed by Connotea which is a Nature product and BibSonomy and 2collab by Elsevier. as the numbers show the first three are comparable in terms of usage but 2collab lacks far behind this is because 2collab is suffering from severe spam attacks and not admitting new users for almost a year now
2collab can be disregarded
Pearson correlation coefficients of the bookmarking indicators with the number of publications and common citation indicators
Usage ratio, Article usage intensity and 5-year Impact Factor correlate highly meaning that a journal with a high IF has many users per article and also a great share of publications being bookmarked
besides that, the other bookmarking indicators show different results
Usage diffusion, i.e. the number of different users correlate highly with the number of documents published in the periodical No correlation between Cited Half-Life and any of the other indicators
Tagcloud: all tags assigned at least 50 times
more tags to recent publications usage increases
tags, that were assigned to articles by users reflect the readers perspective of journal content if they are analyzed over time, shifts of focuses can be revealed Condensed matter = macroscopic and microscopic physical properties of matter static electricity diffusion colloid = high energy particle with large surfaces DMS = dilute magnetic semiconductors graphene = carbon crystal
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