| Title |
Quantifying the economic impact of disasters on businesses using human mobility data: a Bayesian causal inference approach
|
|---|---|
| Published in |
EPJ Data Science, December 2020
|
| DOI | 10.1140/epjds/s13688-020-00255-6 |
| Authors |
Takahiro Yabe, Yunchang Zhang, Satish V. Ukkusuri |
X Demographics
The data shown below were collected from the profiles of 10 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 Kingdom | 2 | 20% |
| Mexico | 1 | 10% |
| India | 1 | 10% |
| Greece | 1 | 10% |
| Chile | 1 | 10% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 50% |
| Scientists | 4 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 86 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 21% |
| Researcher | 9 | 10% |
| Student > Master | 9 | 10% |
| Student > Doctoral Student | 9 | 10% |
| Lecturer | 4 | 5% |
| Other | 15 | 17% |
| Unknown | 22 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 15 | 17% |
| Computer Science | 8 | 9% |
| Social Sciences | 7 | 8% |
| Business, Management and Accounting | 6 | 7% |
| Environmental Science | 5 | 6% |
| Other | 17 | 20% |
| Unknown | 28 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 07 January 2021.
All research outputs
#6,189,714
of 23,267,128 outputs
Outputs from EPJ Data Science
#295
of 382 outputs
Outputs of similar age
#150,823
of 509,311 outputs
Outputs of similar age from EPJ Data Science
#8
of 10 outputs
Altmetric has tracked 23,267,128 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 382 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.7. This one is in the 21st percentile – i.e., 21% 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 509,311 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 70% 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 2 of them.