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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Influenza Forecasting with Google Flu Trends
|
|---|---|
| Published in |
PLOS ONE, February 2013
|
| DOI | 10.1371/journal.pone.0056176 |
| Pubmed ID | |
| Authors |
Andrea Freyer Dugas, Mehdi Jalalpour, Yulia Gel, Scott Levin, Fred Torcaso, Takeru Igusa, Richard E. Rothman |
| Abstract |
We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy. |
X Demographics
The data shown below were collected from the profiles of 18 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 | 4 | 22% |
| Switzerland | 1 | 6% |
| Spain | 1 | 6% |
| Canada | 1 | 6% |
| Unknown | 11 | 61% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 78% |
| Scientists | 4 | 22% |
Mendeley readers
The data shown below were compiled from readership statistics for 305 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 1% |
| United Kingdom | 3 | <1% |
| Japan | 2 | <1% |
| Indonesia | 1 | <1% |
| Malaysia | 1 | <1% |
| Chile | 1 | <1% |
| Israel | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 291 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 62 | 20% |
| Student > Ph. D. Student | 61 | 20% |
| Researcher | 42 | 14% |
| Student > Bachelor | 25 | 8% |
| Other | 15 | 5% |
| Other | 56 | 18% |
| Unknown | 44 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 69 | 23% |
| Medicine and Dentistry | 48 | 16% |
| Mathematics | 22 | 7% |
| Agricultural and Biological Sciences | 20 | 7% |
| Business, Management and Accounting | 18 | 6% |
| Other | 69 | 23% |
| Unknown | 59 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 48. 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 09 May 2023.
All research outputs
#892,840
of 25,863,888 outputs
Outputs from PLOS ONE
#11,611
of 225,571 outputs
Outputs of similar age
#7,363
of 298,576 outputs
Outputs of similar age from PLOS ONE
#252
of 5,172 outputs
Altmetric has tracked 25,863,888 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 225,571 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.9. This one has done particularly well, scoring higher than 94% 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 298,576 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 97% of its contemporaries.
We're also able to compare this research output to 5,172 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.