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X Demographics
Mendeley readers
Chapter title |
A Hierarchical Topic Modelling Approach for Tweet Clustering
|
---|---|
Chapter number | 30 |
Book title |
Social Informatics
|
Published by |
Springer, Cham, September 2017
|
DOI | 10.1007/978-3-319-67256-4_30 |
Book ISBNs |
978-3-31-967255-7, 978-3-31-967256-4
|
Authors |
Bo Wang, Maria Liakata, Arkaitz Zubiaga, Rob Procter |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 67% |
United States | 1 | 17% |
Slovenia | 1 | 17% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 50% |
Members of the public | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 60 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 15% |
Student > Bachelor | 9 | 15% |
Student > Master | 6 | 10% |
Researcher | 3 | 5% |
Student > Doctoral Student | 3 | 5% |
Other | 3 | 5% |
Unknown | 27 | 45% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 19 | 32% |
Engineering | 4 | 7% |
Business, Management and Accounting | 2 | 3% |
Linguistics | 1 | 2% |
Mathematics | 1 | 2% |
Other | 4 | 7% |
Unknown | 29 | 48% |