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Text Mining and Quantitative Research of Medical Service Policy: Sichuan Province as an Example

Overview of attention for article published in Frontiers in Public Health, January 2021
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Mentioned by

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1 X user

Citations

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7 Dimensions

Readers on

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34 Mendeley
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Title
Text Mining and Quantitative Research of Medical Service Policy: Sichuan Province as an Example
Published in
Frontiers in Public Health, January 2021
DOI 10.3389/fpubh.2020.509842
Pubmed ID
Authors

Huiqin Zhang, Liping Zhu, Chen Zeng, Xudong Chen

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 9%
Lecturer 2 6%
Student > Doctoral Student 2 6%
Student > Bachelor 1 3%
Lecturer > Senior Lecturer 1 3%
Other 2 6%
Unknown 23 68%
Readers by discipline Count As %
Medicine and Dentistry 3 9%
Environmental Science 2 6%
Engineering 2 6%
Business, Management and Accounting 1 3%
Economics, Econometrics and Finance 1 3%
Other 3 9%
Unknown 22 65%
Attention Score in Context

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 14 January 2021.
All research outputs
#20,679,788
of 23,274,744 outputs
Outputs from Frontiers in Public Health
#7,977
of 10,749 outputs
Outputs of similar age
#429,164
of 502,662 outputs
Outputs of similar age from Frontiers in Public Health
#342
of 408 outputs
Altmetric has tracked 23,274,744 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,749 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one is in the 1st percentile – i.e., 1% 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 502,662 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 408 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.