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Educational Anomaly Analytics: Features, Methods, and Challenges

Overview of attention for article published in Frontiers in Big Data, January 2022
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2 X users

Citations

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Readers on

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56 Mendeley
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Title
Educational Anomaly Analytics: Features, Methods, and Challenges
Published in
Frontiers in Big Data, January 2022
DOI 10.3389/fdata.2021.811840
Pubmed ID
Authors

Teng Guo, Xiaomei Bai, Xue Tian, Selena Firmin, Feng Xia

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 5 9%
Student > Ph. D. Student 4 7%
Other 3 5%
Student > Doctoral Student 3 5%
Researcher 3 5%
Other 10 18%
Unknown 28 50%
Readers by discipline Count As %
Computer Science 8 14%
Unspecified 5 9%
Sports and Recreations 3 5%
Medicine and Dentistry 3 5%
Social Sciences 3 5%
Other 7 13%
Unknown 27 48%