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Using Deep Learning Models for Multimodal Sentence Level Sentiment Analysis of Sign Language

Overview of attention for article published in Forum for Linguistic Studies, April 2025
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1 X user

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9 Mendeley
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Article details
Title
Using Deep Learning Models for Multimodal Sentence Level Sentiment Analysis of Sign Language
Published in
Forum for Linguistic Studies, April 2025
DOI 10.30564/fls.v7i4.9041
Authors

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Timeline Attention over time Attention Score history
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Activity
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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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Lecturer 2 22%
Student > Master 2 22%
Unspecified 1 11%
Unknown 4 44%
Readers by discipline
Readers by discipline Count As %
Social Sciences 2 22%
Unspecified 1 11%
Computer Science 1 11%
Materials Science 1 11%
Unknown 4 44%
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 27 August 2025.
All research outputs
#24,049,117
of 29,293,342 outputs
Outputs from Forum for Linguistic Studies
#65
of 105 outputs
Outputs of similar age
#239,615
of 322,494 outputs
Outputs of similar age from Forum for Linguistic Studies
#15
of 24 outputs
Altmetric has tracked 29,293,342 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 105 research outputs from this source. They receive a mean Attention Score of 1.1. 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 322,494 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 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.