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Development of a patients’ satisfaction analysis system using machine learning and lexicon-based methods

Overview of attention for article published in BMC Health Services Research, March 2023
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1 X user

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21 Mendeley
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Title
Development of a patients’ satisfaction analysis system using machine learning and lexicon-based methods
Published in
BMC Health Services Research, March 2023
DOI 10.1186/s12913-023-09260-7
Pubmed ID
Authors

Shiva Khaleghparast, Majid Maleki, Ghasem Hajianfar, Esmaeil Soumari, Mehrdad Oveisi, Hassan Maleki Golandouz, Feridoun Noohi, Maziar Gholampour dehaki, Reza Golpira, Saeideh Mazloomzadeh, Maedeh Arabian, Samira Kalayinia

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

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 10%
Student > Master 2 10%
Student > Doctoral Student 1 5%
Unspecified 1 5%
Unknown 15 71%
Readers by discipline Count As %
Computer Science 5 24%
Unspecified 1 5%
Unknown 15 71%
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 21 November 2023.
All research outputs
#16,896,029
of 24,842,061 outputs
Outputs from BMC Health Services Research
#6,168
of 8,401 outputs
Outputs of similar age
#238,197
of 408,242 outputs
Outputs of similar age from BMC Health Services Research
#128
of 194 outputs
Altmetric has tracked 24,842,061 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,401 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 16th percentile – i.e., 16% 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 408,242 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 194 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.