NotiMind: responses to smartphone notifications as affective sensors

Kanjo, E ORCID: https://orcid.org/0000-0002-1720-0661, Kuss, DJ ORCID: https://orcid.org/0000-0001-8917-782X and Ang, CS, 2017. NotiMind: responses to smartphone notifications as affective sensors. IEEE Access, 5, pp. 22023-22035. ISSN 2169-3536

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Abstract

Today's mobile phone users are faced with large numbers of notifications on social media, ranging from new followers on Twitter and emails to messages received from WhatsApp and Facebook. These digital alerts continuously disrupt activities through instant calls for attention. This paper examines closely the way everyday users interact with notifications and their impact on users’ emotion. Fifty users were recruited to download our application NotiMind and use it over a five-week period. Users’ phones collected thousands of social and system notifications along with affect data collected via self-reported PANAS tests three times a day. Results showed a noticeable correlation between positive affective measures and keyboard activities. When large numbers of Post and Remove notifications occur, a corresponding increase in negative affective measures is detected. Our predictive model has achieved a good accuracy level using three different classifiers "in the wild" (F-measure 74-78% within-subject model, 72-76% global model). Our findings show that it is possible to automatically predict when people are experiencing positive, neutral or negative affective states based on interactions with notifications. We also show how our findings open the door to a wide range of applications in relation to emotion awareness on social and mobile communication.

Item Type:	Journal article
Publication Title:	IEEE Access
Creators:	Kanjo, E., Kuss, D.J. and Ang, C.S.
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Date:	2017
Volume:	5
ISSN:	2169-3536
Identifiers:	Number Type 10.1109/ACCESS.2017.2755661 DOI
Divisions:	Schools > School of Science and Technology Schools > School of Social Sciences
Record created by:	Linda Sullivan
Date Added:	22 Sep 2017 11:08
Last Modified:	24 Jan 2018 14:50
URI:	https://irep.ntu.ac.uk/id/eprint/31674

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