↓ Skip to main content

The Effectiveness of Morphology-aware Segmentation in Low-Resource Neural Machine Translation

Overview of attention for article published in arXiv, January 2021
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

twitter
4 X users

Readers on

mendeley
76 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.
Article details
Title
The Effectiveness of Morphology-aware Segmentation in Low-Resource Neural Machine Translation
Published in
arXiv, January 2021
DOI 10.18653/v1/2021.eacl-srw.22
Authors

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 9 12%
Student > Bachelor 7 9%
Student > Master 6 8%
Researcher 4 5%
Lecturer 3 4%
Other 7 9%
Unknown 40 53%
Readers by discipline
Readers by discipline Count As %
Computer Science 17 22%
Linguistics 7 9%
Engineering 2 3%
Arts and Humanities 1 1%
Unspecified 1 1%
Other 5 7%
Unknown 43 57%
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 24 March 2021.
All research outputs
#17,692,096
of 25,936,091 outputs
Outputs from arXiv
#368,143
of 956,745 outputs
Outputs of similar age
#334,545
of 531,141 outputs
Outputs of similar age from arXiv
#9,914
of 24,596 outputs
Altmetric has tracked 25,936,091 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 956,745 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 54% of its peers.
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 531,141 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24,596 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.