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X Demographics
Mendeley readers
Chapter title |
Computational Climate Change: How Data Science and Numerical Models Can Help Build Good Climate Policies and Practices
|
---|---|
Chapter number | 14 |
Book title |
Handbook of Computational Social Science for Policy
|
Published by |
Springer, Cham, January 2023
|
DOI | 10.1007/978-3-031-16624-2_14 |
Book ISBNs |
978-3-03-116623-5, 978-3-03-116624-2
|
Authors |
Tavoni, Massimo |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Italy | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 3 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 1 | 33% |
Student > Master | 1 | 33% |
Unknown | 1 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Environmental Science | 1 | 33% |
Energy | 1 | 33% |
Unknown | 1 | 33% |