EmotionSensing: predicting mobile user emotions

Mahnaz Roshanaei, Richard Han, Shivakant Mishra

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

4 Citations (Scopus)

Abstract

User emotions are important contextual features in building context-aware pervasive applications. In this paper, we explore the question of whether it is possible to predict user emotions from their smartphone activities. To get the ground truth data, we have built an Android app that collects user emotions along with a number of features including their current location, activity they are engaged in, and smartphones apps they are currently running. We deployed this app for over a period of three months and collected a large amount of useful user data. We describe the details of this data in terms of statistics and user behaviors, provide a detailed analysis in terms of correlations between user emotions and other features, and finally build classifiers to predict user emotions. Performance of these classifiers is quite promising with high accuracy. We describe the details of these classifiers along with the results.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
EditorsJana Diesner, Elena Ferrari, Guandong Xu
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery, Inc
Pages325-330
Number of pages6
ISBN (Electronic)9781450349932
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 - Sydney, Australia
Duration: 31 Jul 20173 Aug 2017

Publication series

NameProceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017

Conference

Conference9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
CountryAustralia
CitySydney
Period31/07/173/08/17

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