↓ Skip to main content

Ascertaining injury risk issues through big data analysis: text-mining based analysis of national emergency response data

Overview of attention for article published in Frontiers in Public Health, February 2024
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
4 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Ascertaining injury risk issues through big data analysis: text-mining based analysis of national emergency response data
Published in
Frontiers in Public Health, February 2024
DOI 10.3389/fpubh.2024.1326457
Pubmed ID
Authors

Jin-Young Won, Yu-Rim Lee, Myeong-Heum Cho, Yun-Tae Kim, Ji-Hyang Lee

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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 50%
Unknown 2 50%
Readers by discipline Count As %
Unspecified 2 50%
Unknown 2 50%
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 28 February 2024.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Frontiers in Public Health
#9,804
of 14,063 outputs
Outputs of similar age
#118,480
of 147,959 outputs
Outputs of similar age from Frontiers in Public Health
#114
of 368 outputs
Altmetric has tracked 25,382,440 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 14,063 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. 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 147,959 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 368 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.