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Mendeley readers
Chapter title |
Text Mining and Real-Time Analytics of Twitter Data: A Case Study of Australian Hay Fever Prediction
|
---|---|
Chapter number | 12 |
Book title |
Health Information Science
|
Published by |
Springer, Cham, September 2018
|
DOI | 10.1007/978-3-030-01078-2_12 |
Book ISBNs |
978-3-03-001077-5, 978-3-03-001078-2
|
Authors |
Sudha Subramani, Sandra Michalska, Hua Wang, Frank Whittaker, Benjamin Heyward, Subramani, Sudha, Michalska, Sandra, Wang, Hua, Whittaker, Frank, Heyward, Benjamin |
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 > Master | 4 | 18% |
Student > Bachelor | 3 | 14% |
Lecturer > Senior Lecturer | 2 | 9% |
Student > Doctoral Student | 1 | 5% |
Lecturer | 1 | 5% |
Other | 4 | 18% |
Unknown | 7 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 7 | 32% |
Business, Management and Accounting | 2 | 9% |
Engineering | 2 | 9% |
Psychology | 1 | 5% |
Philosophy | 1 | 5% |
Other | 0 | 0% |
Unknown | 9 | 41% |