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Twitter Demographics
Mendeley readers
Chapter title |
Squerall: Virtual Ontology-Based Access to Heterogeneous and Large Data Sources
|
---|---|
Chapter number | 15 |
Book title |
The Semantic Web – ISWC 2019
|
Published by |
Springer, Cham, October 2019
|
DOI | 10.1007/978-3-030-30796-7_15 |
Book ISBNs |
978-3-03-030795-0, 978-3-03-030796-7
|
Authors |
Mohamed Nadjib Mami, Damien Graux, Simon Scerri, Hajira Jabeen, Sören Auer, Jens Lehmann, Mami, Mohamed Nadjib, Graux, Damien, Scerri, Simon, Jabeen, Hajira, Auer, Sören, Lehmann, Jens |
Twitter Demographics
The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 30 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 6 | 20% |
Student > Doctoral Student | 5 | 17% |
Researcher | 4 | 13% |
Student > Bachelor | 3 | 10% |
Student > Postgraduate | 2 | 7% |
Other | 3 | 10% |
Unknown | 7 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 22 | 73% |
Engineering | 1 | 3% |
Unknown | 7 | 23% |