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Mendeley readers
Chapter title |
Real-Time Sentiment-Based Anomaly Detection in Twitter Data Streams
|
---|---|
Chapter number | 17 |
Book title |
Advances in Artificial Intelligence
|
Published by |
Springer, Cham, June 2015
|
DOI | 10.1007/978-3-319-18356-5_17 |
Book ISBNs |
978-3-31-918355-8, 978-3-31-918356-5
|
Authors |
Khantil Patel, Orland Hoeber, Howard J. Hamilton |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 26 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 6 | 23% |
Researcher | 5 | 19% |
Student > Bachelor | 3 | 12% |
Student > Doctoral Student | 2 | 8% |
Other | 2 | 8% |
Other | 7 | 27% |
Unknown | 1 | 4% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 18 | 69% |
Medicine and Dentistry | 2 | 8% |
Linguistics | 1 | 4% |
Unspecified | 1 | 4% |
Social Sciences | 1 | 4% |
Other | 1 | 4% |
Unknown | 2 | 8% |