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Tweets as Impact Indicators: Examining the Implications of Automated “bot” Accounts on Twitter

Overview of attention for article published in this source, May 2015
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Mentioned by

blogs
3 blogs
policy
1 policy source
twitter
85 X users

Citations

dimensions_citation
170 Dimensions

Readers on

mendeley
299 Mendeley
citeulike
2 CiteULike
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Title
Tweets as Impact Indicators: Examining the Implications of Automated “bot” Accounts on Twitter
Published by
Wiley, May 2015
DOI 10.1002/asi.23456
Authors

Stefanie Haustein, Timothy D. Bowman, Kim Holmberg, Andrew Tsou, Cassidy R. Sugimoto, Vincent Larivière

X Demographics

X Demographics

The data shown below were collected from the profiles of 85 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 299 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 4 1%
Germany 3 1%
Netherlands 3 1%
United States 3 1%
United Kingdom 3 1%
Malaysia 2 <1%
Spain 2 <1%
France 1 <1%
Denmark 1 <1%
Other 4 1%
Unknown 273 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 17%
Student > Master 44 15%
Student > Bachelor 37 12%
Librarian 32 11%
Researcher 24 8%
Other 55 18%
Unknown 55 18%
Readers by discipline Count As %
Computer Science 79 26%
Social Sciences 73 24%
Business, Management and Accounting 17 6%
Arts and Humanities 11 4%
Medicine and Dentistry 10 3%
Other 46 15%
Unknown 63 21%