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Software Engineering Through Community-Engaged Learning and an Inclusive Network

Overview of attention for article published in arXiv, February 2023
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Title
Software Engineering Through Community-Engaged Learning and an Inclusive Network
Published in
arXiv, February 2023
DOI 10.1007/978-1-4842-9651-6_26
Authors

Nowshin Nawar Arony, Kezia Devathasan, Ze Shi Li, Daniela Damian

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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 September 2024.
All research outputs
#20,633,834
of 26,345,808 outputs
Outputs from arXiv
#459,229
of 1,019,237 outputs
Outputs of similar age
#355,256
of 500,667 outputs
Outputs of similar age from arXiv
#13,237
of 30,234 outputs
Altmetric has tracked 26,345,808 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,019,237 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 45th percentile – i.e., 45% 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 500,667 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30,234 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.