| Title |
A roadmap for the computation of persistent homology
|
|---|---|
| Published in |
EPJ Data Science, August 2017
|
| DOI | 10.1140/epjds/s13688-017-0109-5 |
| Pubmed ID | |
| Authors |
Nina Otter, Mason A Porter, Ulrike Tillmann, Peter Grindrod, Heather A Harrington |
X Demographics
The data shown below were collected from the profiles of 53 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 17% |
| United Kingdom | 5 | 9% |
| Italy | 3 | 6% |
| Japan | 3 | 6% |
| Finland | 2 | 4% |
| Spain | 2 | 4% |
| France | 2 | 4% |
| Belgium | 1 | 2% |
| Chile | 1 | 2% |
| Other | 6 | 11% |
| Unknown | 19 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 29 | 55% |
| Members of the public | 23 | 43% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 452 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | <1% |
| United States | 2 | <1% |
| Singapore | 1 | <1% |
| Slovenia | 1 | <1% |
| Poland | 1 | <1% |
| Unknown | 445 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 100 | 22% |
| Researcher | 71 | 16% |
| Student > Master | 44 | 10% |
| Student > Bachelor | 30 | 7% |
| Professor | 21 | 5% |
| Other | 84 | 19% |
| Unknown | 102 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 92 | 20% |
| Computer Science | 71 | 16% |
| Physics and Astronomy | 45 | 10% |
| Engineering | 35 | 8% |
| Neuroscience | 18 | 4% |
| Other | 74 | 16% |
| Unknown | 117 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 51. 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 17 January 2023.
All research outputs
#791,285
of 24,796,678 outputs
Outputs from EPJ Data Science
#55
of 418 outputs
Outputs of similar age
#16,698
of 322,750 outputs
Outputs of similar age from EPJ Data Science
#5
of 11 outputs
Altmetric has tracked 24,796,678 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 418 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 40.8. This one has done well, scoring higher than 87% 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 322,750 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 11 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 63% of its contemporaries.