Title
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. We would like to achieve better accuracies and this study is a first step towards seeing how to model such data.
Year
DOI
Venue
2018
10.1145/3210240.3210823
MobiSys '18: The 16th Annual International Conference on Mobile Systems, Applications, and Services Munich Germany June, 2018
Field
DocType
ISBN
Big Five personality traits,Decision tree,Binary classification,Inference,Computer science,Support vector machine,Real-time computing,Artificial intelligence,Personality psychology,Machine learning,Personality
Conference
978-1-4503-5720-3
Citations 
PageRank 
References 
1
0.36
1
Authors
7
Name
Order
Citations
PageRank
Catherine Tong1160.99
Gabriella M. Harari211.04
Angela Chieh321.39
Otmane Bellahsen410.70
Matthieu Vegreville541.40
Eva Roitmann610.36
Nicholas D. Lane74247248.15