STM social bookmarking (by S. Haustein)
•Transferir como PPT, PDF•
4 gostaram•1,657 visualizações
![Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recomendados
Recomendados
Mais conteúdo relacionado
Semelhante a STM social bookmarking (by S. Haustein)
Semelhante a STM social bookmarking (by S. Haustein) (20)
Último
Último (20)
STM social bookmarking (by S. Haustein)
- 1. Journal Evaluation and Science 2.0 Using Social Bookmarks to Analyze Reader Perception | Stefanie Haustein, Evgeni Golov, Kathleen Luckanus, Sabrina Reher & Jens Terliesner
- 6. Introduction: Social Bookmarking in STM
- 7. Introduction: Social Bookmarking in STM
- 8. Introduction: Social Bookmarking in STM
- 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
- 21. Journal Evaluation: Usage Indicators Pearson correlation Usage ratio Usage diffusion Article usage intensity Journal usage intensity P 5-year IF h-index Cited Half-Life Usage ratio 0.33 0.90 -0.22 -0.09 0.86 0.50 0.02 Usage diffusion 0.33 0.27 0.45 0.72 0.14 0.78 -0.24 Article usage intensity 0.90 0.27 -0.36 -0.16 0.88 0.46 0.09 Journal usage intensity -0.22 0.45 -0.36 0.77 -0.29 0.40 -0.10 P -0.09 0.72 -0.16 0.77 -0.16 0.69 -0.17 5-year IF 0.86 0.14 0.88 -0.29 -0.16 0.39 0.21 h-index 0.50 0.78 0.46 0.40 0.69 0.39 -0.22 Cited Half-Life 0.02 -0.24 0.09 -0.10 -0.17 0.21 -0.22
- 22. Journal Evaluation: Usage Indicators Pearson correlation Usage ratio Usage diffusion Article usage intensity Journal usage intensity P 5-year IF h-index Cited Half-Life Usage ratio 0.33 0.90 -0.22 -0.09 0.86 0.50 0.02 Usage diffusion 0.33 0.27 0.45 0.72 0.14 0.78 -0.24 Article usage intensity 0.90 0.27 -0.36 -0.16 0.88 0.46 0.09 Journal usage intensity -0.22 0.45 -0.36 0.77 -0.29 0.40 -0.10 P -0.09 0.72 -0.16 0.77 -0.16 0.69 -0.17 5-year IF 0.86 0.14 0.88 -0.29 -0.16 0.39 0.21 h-index 0.50 0.78 0.46 0.40 0.69 0.39 -0.22 Cited Half-Life 0.02 -0.24 0.09 -0.10 -0.17 0.21 -0.22
- 23. Journal Evaluation: Usage Indicators Pearson correlation Usage ratio Usage diffusion Article usage intensity Journal usage intensity P 5-year IF h-index Cited Half-Life Usage ratio 0.33 0.90 -0.22 -0.09 0.86 0.50 0.02 Usage diffusion 0.33 0.27 0.45 0.72 0.14 0.78 -0.24 Article usage intensity 0.90 0.27 -0.36 -0.16 0.88 0.46 0.09 Journal usage intensity -0.22 0.45 -0.36 0.77 -0.29 0.40 -0.10 P -0.09 0.72 -0.16 0.77 -0.16 0.69 -0.17 5-year IF 0.86 0.14 0.88 -0.29 -0.16 0.39 0.21 h-index 0.50 0.78 0.46 0.40 0.69 0.39 -0.22 Cited Half-Life 0.02 -0.24 0.09 -0.10 -0.17 0.21 -0.22
- 24. Journal Evaluation: Usage Indicators Pearson correlation Usage ratio Usage diffusion Article usage intensity Journal usage intensity P 5-year IF h-index Cited Half-Life Usage ratio 0.33 0.90 -0.22 -0.09 0.86 0.50 0.02 Usage diffusion 0.33 0.27 0.45 0.72 0.14 0.78 -0.24 Article usage intensity 0.90 0.27 -0.36 -0.16 0.88 0.46 0.09 Journal usage intensity -0.22 0.45 -0.36 0.77 -0.29 0.40 -0.10 P -0.09 0.72 -0.16 0.77 -0.16 0.69 -0.17 5-year IF 0.86 0.14 0.88 -0.29 -0.16 0.39 0.21 h-index 0.50 0.78 0.46 0.40 0.69 0.39 -0.22 Cited Half-Life 0.02 -0.24 0.09 -0.10 -0.17 0.21 -0.22
- 26. Journal Evaluation: Tags number of unique tags Number of tags per publication year for all bookmarked articles
Notas do Editor
- 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