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Inference of big-five personality using large-scale networked mobile and appliance Data

Abstract:

We present the first large-scale (9270-user) study of data from both mobile and networked appliances for Big-Five personality inference. We correlate aggregated behavioral and physical health features with personalities, and perform binary classification using SVM and Decision Tree. We find that it is possible to infer each Big-Five personality at accuracies of 75% from this dataset despite its size and complexity (mix of mobile and appliance) as prior methods offer similar accuracy levels. W...

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Publication status:
Published
Peer review status:
Reviewed (other)

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Publisher copy:
10.1145/3210240.3210823

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Publisher:
Association for Computing Machinery Publisher's website
Pages:
530
Publication date:
2018-06-10
Acceptance date:
2018-03-01
DOI:
Pubs id:
pubs:912061
URN:
uri:288035fa-da27-41e1-9486-f113116b4ca6
UUID:
uuid:288035fa-da27-41e1-9486-f113116b4ca6
Local pid:
pubs:912061
ISBN:
9781450357203

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