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Mendeley readers
| Title |
An unsupervised method for social network spammer detection based on user information interests
|
|---|---|
| Published in |
Journal of Big Data, January 2022
|
| DOI | 10.1186/s40537-021-00552-5 |
| Authors |
Darshika Koggalahewa, Yue Xu, Ernest Foo |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 11% |
| Student > Master | 4 | 11% |
| Librarian | 1 | 3% |
| Other | 1 | 3% |
| Professor | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 22 | 61% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 19% |
| Arts and Humanities | 2 | 6% |
| Engineering | 2 | 6% |
| Agricultural and Biological Sciences | 1 | 3% |
| Chemistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 22 | 61% |