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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Text classification models for the automatic detection of nonmedical prescription medication use from social media
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, January 2021
|
| DOI | 10.1186/s12911-021-01394-0 |
| Pubmed ID | |
| Authors |
Mohammed Ali Al-Garadi, Yuan-Chi Yang, Haitao Cai, Yucheng Ruan, Karen O’Connor, Gonzalez-Hernandez Graciela, Jeanmarie Perrone, Abeed Sarker |
X Demographics
The data shown below were collected from the profiles of 4 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 | 2 | 50% |
| France | 1 | 25% |
| Brazil | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 103 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 11% |
| Student > Ph. D. Student | 10 | 10% |
| Student > Bachelor | 8 | 8% |
| Researcher | 7 | 7% |
| Lecturer | 7 | 7% |
| Other | 21 | 20% |
| Unknown | 39 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 28 | 27% |
| Medicine and Dentistry | 8 | 8% |
| Engineering | 6 | 6% |
| Nursing and Health Professions | 5 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 2% |
| Other | 8 | 8% |
| Unknown | 46 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 08 April 2022.
All research outputs
#13,625,587
of 23,506,079 outputs
Outputs from BMC Medical Informatics and Decision Making
#964
of 2,025 outputs
Outputs of similar age
#238,211
of 506,714 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#31
of 69 outputs
Altmetric has tracked 23,506,079 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,025 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 51% 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 506,714 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 52% of its contemporaries.
We're also able to compare this research output to 69 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 56% of its contemporaries.