| Title |
Topic discovery and future trend forecasting for texts
|
|---|---|
| Published in |
Journal of Big Data, April 2016
|
| DOI | 10.1186/s40537-016-0039-2 |
| Authors |
Jose L. Hurtado, Ankur Agarwal, Xingquan Zhu |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Greece | 1 | 1% |
| Canada | 1 | 1% |
| Switzerland | 1 | 1% |
| Unknown | 78 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 27% |
| Student > Master | 18 | 22% |
| Student > Bachelor | 7 | 9% |
| Researcher | 5 | 6% |
| Other | 4 | 5% |
| Other | 10 | 12% |
| Unknown | 15 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 40 | 49% |
| Business, Management and Accounting | 9 | 11% |
| Engineering | 3 | 4% |
| Economics, Econometrics and Finance | 2 | 2% |
| Social Sciences | 2 | 2% |
| Other | 6 | 7% |
| Unknown | 19 | 23% |