↓ Skip to main content

BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices

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

Mentioned by

facebook
1 Facebook page

Readers on

mendeley
8 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
BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices
Published in
Frontiers in Public Health, April 2024
DOI 10.3389/fpubh.2024.1392180
Pubmed ID
Authors

Fan Dong, Wenjing Guo, Jie Liu, Tucker A. Patterson, Huixiao Hong

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 8 100%
Readers by discipline Count As %
Unspecified 8 100%
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 10 May 2024.
All research outputs
#23,223,250
of 25,882,826 outputs
Outputs from Frontiers in Public Health
#10,091
of 14,457 outputs
Outputs of similar age
#165,222
of 207,275 outputs
Outputs of similar age from Frontiers in Public Health
#129
of 258 outputs
Altmetric has tracked 25,882,826 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 14,457 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. 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 207,275 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 258 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.