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Use of scientific social networking to improve the research strategies of PubMed readers

Overview of attention for article published in BMC Research Notes, February 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
27 Mendeley
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Title
Use of scientific social networking to improve the research strategies of PubMed readers
Published in
BMC Research Notes, February 2016
DOI 10.1186/s13104-016-1920-y
Pubmed ID
Authors

Pavel Evdokimov, Alexey Kudryavtsev, Ekaterina Ilgisonis, Elena Ponomarenko, Andrey Lisitsa

Abstract

Keeping up with journal articles on a daily basis is an important activity of scientists engaged in biomedical research. Usually, journal articles and papers in the field of biomedicine are accessed through the Medline/PubMed electronic library. In the process of navigating PubMed, researchers unknowingly generate user-specific reading profiles that can be shared within a social networking environment. This paper examines the structure of the social networking environment generated by PubMed users. A web browser plugin was developed to map [in Medical Subject Headings (MeSH) terms] the reading patterns of individual PubMed users. We developed a scientific social network based on the personal research profiles of readers of biomedical articles. A browser plugin is used to record the digital object identifier or PubMed ID of web pages. Recorded items are posted on the activity feed and automatically mapped to PubMed abstract. Within the activity feed a user can trace back previously browsed articles and insert comments. By calculating the frequency with which specific MeSH occur, the research interests of PubMed users can be visually represented with a tag cloud. Finally, research profiles can be searched for matches between network users. A social networking environment was created using MeSH terms to map articles accessed through the Medline/PubMed online library system. In-network social communication is supported by the recommendation of articles and by matching users with similar scientific interests. The system is available at http://bioknol.org/en/ .

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 22%
Researcher 4 15%
Student > Master 4 15%
Student > Ph. D. Student 3 11%
Student > Postgraduate 2 7%
Other 6 22%
Unknown 2 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 19%
Medicine and Dentistry 3 11%
Social Sciences 3 11%
Nursing and Health Professions 3 11%
Engineering 2 7%
Other 7 26%
Unknown 4 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 November 2016.
All research outputs
#5,685,727
of 17,658,188 outputs
Outputs from BMC Research Notes
#979
of 3,696 outputs
Outputs of similar age
#90,938
of 271,349 outputs
Outputs of similar age from BMC Research Notes
#1
of 1 outputs
Altmetric has tracked 17,658,188 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 3,696 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 271,349 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them