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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Differentiating Sub-groups of Online Depression-Related Communities Using Textual Cues
|
|---|---|
| Chapter number | 17 |
| Book title |
Web Information Systems Engineering – WISE 2015
|
| Published in |
Lecture notes in computer science, December 2015
|
| DOI | 10.1007/978-3-319-26187-4_17 |
| Book ISBNs |
978-3-31-926186-7, 978-3-31-926187-4
|
| Authors |
Nguyen, Thin, O’Dea, Bridianne, Larsen, Mark, Phung, Dinh, Venkatesh, Svetha, Christensen, Helen, Thin Nguyen, Bridianne O’Dea, Mark Larsen, Dinh Phung, Svetha Venkatesh, Helen Christensen |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 4 | 67% |
| United States | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 18% |
| Student > Doctoral Student | 3 | 14% |
| Researcher | 3 | 14% |
| Student > Master | 2 | 9% |
| Professor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 8 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 23% |
| Psychology | 3 | 14% |
| Arts and Humanities | 1 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Nursing and Health Professions | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 8 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 26 November 2015.
All research outputs
#6,939,948
of 23,253,955 outputs
Outputs from Lecture notes in computer science
#2,222
of 8,158 outputs
Outputs of similar age
#108,096
of 390,283 outputs
Outputs of similar age from Lecture notes in computer science
#248
of 530 outputs
Altmetric has tracked 23,253,955 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 8,158 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 72% 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 390,283 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 72% of its contemporaries.
We're also able to compare this research output to 530 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 53% of its contemporaries.