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Special issue of BMC medical informatics and decision making on health natural language processing

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
11 Mendeley
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Title
Special issue of BMC medical informatics and decision making on health natural language processing
Published in
BMC Medical Informatics and Decision Making, April 2019
DOI 10.1186/s12911-019-0777-0
Pubmed ID
Authors

V. G. Vinod Vydiswaran, Yaoyun Zhang, Yanshan Wang, Hua Xu

Twitter Demographics

The data shown below were collected from the profiles of 2 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 27%
Student > Ph. D. Student 2 18%
Professor 1 9%
Researcher 1 9%
Professor > Associate Professor 1 9%
Other 0 0%
Unknown 3 27%
Readers by discipline Count As %
Computer Science 5 45%
Linguistics 1 9%
Psychology 1 9%
Medicine and Dentistry 1 9%
Unknown 3 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 April 2019.
All research outputs
#11,097,515
of 14,596,192 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,034
of 1,339 outputs
Outputs of similar age
#182,372
of 265,840 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#3
of 18 outputs
Altmetric has tracked 14,596,192 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,339 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 265,840 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.