Text Mining for Information Professionals
Springer International Publishing
Title |
Text Mining for Information Professionals
|
---|---|
Published by |
Springer International Publishing, January 2022
|
DOI | 10.1007/978-3-030-85085-2 |
ISBNs |
978-3-03-085084-5, 978-3-03-085085-2
|
Authors |
Manika Lamba, Margam Madhusudhan |
Country | Count | As % |
---|---|---|
Germany | 4 | 11% |
India | 3 | 8% |
United States | 2 | 5% |
Spain | 2 | 5% |
Australia | 2 | 5% |
Eswatini | 1 | 3% |
United Kingdom | 1 | 3% |
Ukraine | 1 | 3% |
Mexico | 1 | 3% |
Other | 4 | 11% |
Unknown | 16 | 43% |
Type | Count | As % |
---|---|---|
Members of the public | 22 | 59% |
Scientists | 9 | 24% |
Science communicators (journalists, bloggers, editors) | 5 | 14% |
Unknown | 1 | 3% |
Country | Count | As % |
---|---|---|
Unknown | 22 | 100% |
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 3 | 14% |
Unspecified | 1 | 5% |
Lecturer > Senior Lecturer | 1 | 5% |
Librarian | 1 | 5% |
Student > Master | 1 | 5% |
Other | 2 | 9% |
Unknown | 13 | 59% |
Readers by discipline | Count | As % |
---|---|---|
Business, Management and Accounting | 3 | 14% |
Social Sciences | 2 | 9% |
Unspecified | 1 | 5% |
Arts and Humanities | 1 | 5% |
Computer Science | 1 | 5% |
Other | 1 | 5% |
Unknown | 13 | 59% |