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Mendeley readers
Chapter title |
Using Geocoding and Topic Extraction to Make Sense of Comments on Social Network Pages of Local Government Agencies
|
---|---|
Chapter number | 22 |
Book title |
Electronic Government
|
Published by |
Springer, Cham, September 2018
|
DOI | 10.1007/978-3-319-98690-6_22 |
Book ISBNs |
978-3-31-998689-0, 978-3-31-998690-6
|
Authors |
Pedro C. R. Lima, Raissa Barcellos, Flavia Bernardini, Jose Viterbo, Lima, Pedro C. R., Barcellos, Raissa, Bernardini, Flavia, Viterbo, Jose |
Mendeley readers
The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 118 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 16 | 14% |
Student > Master | 14 | 12% |
Student > Doctoral Student | 13 | 11% |
Researcher | 11 | 9% |
Student > Postgraduate | 5 | 4% |
Other | 18 | 15% |
Unknown | 41 | 35% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 22 | 19% |
Social Sciences | 16 | 14% |
Business, Management and Accounting | 14 | 12% |
Arts and Humanities | 4 | 3% |
Decision Sciences | 3 | 3% |
Other | 14 | 12% |
Unknown | 45 | 38% |