University of Oulu

Prediction of big five personality traits from mobile application usage

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Author: Sharmila, Parsa1
Organizations: 1University of Oulu, Faculty of Information Technology and Electrical Engineering, Computer Science
Format: ebook
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.1 MB)
Pages: 72
Persistent link: http://urn.fi/URN:NBN:fi:oulu-202006242651
Language: English
Published: Oulu : P. Sharmila, 2020
Publish Date: 2020-06-30
Thesis type: Master's thesis
Tutor: Peltonen, Ella
Reviewer: Pirttikangas, Susanna
Peltonen, Ella
Description:

Abstract

Smartphones evolved being an integral part of our daily lives and in recent days. Studies show that smartphone usage is correlated to user personality traits. This critical ecosystem is dependent on several variables such as geographic location, demographic traits, ethnic impact or cultural influence and so on. While significant number of demographic, environmental and medical analysis is done based on smartphone usage, there are inadequate amount of study carried out to analyse human personality. All of these information provide pivotal insights for improving user experience, creating recommendations, identifying marketing strategies and for a general overall usage improvement. This study is done with application usage data collected over 6 months from 739 Android smartphone users along with a 50-item Big Five Personality Trait questionnaire. The analysis focuses on the fact that, category-level aggregated application usage is enough for predicting Big Five personality traits achieving 9–14% error which is 86–91% accuracy on average. This study concludes that user personality generates a fundamental impact on smartphone application and application category usage. This work reflects the possible personality-driven research in future and depicts the significance and involvement of application categories in achieving proper accuracy in general traits, while pursuing for personality study.

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Copyright information: © Parsa Sharmila, 2020. This publication is copyrighted. You may download, display and print it for your own personal use. Commercial use is prohibited.