You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
| Chapter title |
Predicting Best Answerers for New Questions: An Approach Leveraging Topic Modeling and Collaborative Voting
|
|---|---|
| Chapter number | 5 |
| Book title |
Social Informatics
|
| Published by |
Springer Berlin Heidelberg, January 2014
|
| DOI | 10.1007/978-3-642-55285-4_5 |
| Book ISBNs |
978-3-64-255284-7, 978-3-64-255285-4
|
| Authors |
Yuan Tian, Pavneet Singh Kochhar, Ee-Peng Lim, Feida Zhu, David Lo |
| Editors |
Akiyo Nadamoto, Adam Jatowt, Adam Wierzbicki, Jochen L. Leidner |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 3% |
| China | 1 | 3% |
| Unknown | 36 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 32% |
| Student > Master | 8 | 21% |
| Lecturer | 3 | 8% |
| Student > Bachelor | 3 | 8% |
| Student > Doctoral Student | 2 | 5% |
| Other | 5 | 13% |
| Unknown | 5 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 28 | 74% |
| Arts and Humanities | 1 | 3% |
| Business, Management and Accounting | 1 | 3% |
| Social Sciences | 1 | 3% |
| Unknown | 7 | 18% |