Studying Complex Adaptive Systems With Internal States: A Recurrence Network Approach to the Analysis of Multivariate Time-Series Data Representing Self-Reports of Human Experience
Published in
Frontiers in Applied Mathematics and Statistics, April 2020
This research output has an Altmetric Attention Score of 6. 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 22 January 2022.
All research outputs
#6,651,509
of 26,592,204 outputs
Outputs from Frontiers in Applied Mathematics and Statistics
#38
of 432 outputs
Outputs of similar age
#125,073
of 407,663 outputs
Outputs of similar age from Frontiers in Applied Mathematics and Statistics
#1
of 10 outputs
Altmetric has tracked 26,592,204 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 432 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done particularly well, scoring higher than 91% 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 407,663 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them
