You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Chapter title |
An Adaptive and Efficient Method for Detecting First Signs of Depression with Information from the Social Web
|
---|---|
Chapter number | 15 |
Book title |
Computer Science – CACIC 2019
|
Published by |
Springer, Cham, October 2019
|
DOI | 10.1007/978-3-030-48325-8_15 |
Book ISBNs |
978-3-03-048324-1, 978-3-03-048325-8
|
Authors |
Leticia C. Cagnina, Marcelo L. Errecalde, Ma. José Garciarena Ucelay, Dario G. Funez, Ma. Paula Villegas, Cagnina, Leticia C., Errecalde, Marcelo L., Garciarena Ucelay, Ma. José, Funez, Dario G., Villegas, Ma. Paula |
Mendeley readers
The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 2 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 1 | 50% |
Unknown | 1 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 1 | 50% |
Unknown | 1 | 50% |