Smartphones have the potential to produce new habits, i.e., habitual phone usage sessions consistently associated with explicit contextual cues. Despite there is evidence that habitual smartphone use is perceived as meaningless and addictive, little is known about what such habits are, how they can be detected, and how their disruptive effect can be mitigated. In this paper, we propose a data analytic methodology based on association rule mining to automatically discover smartphone habits from smartphone usage data. By assessing the methodology with more than 130,000 smartphone sessions collected in-the-wild, we show evidence that smartphone use can be characterized by different types of complex habits, which are highly diversified across users and involve multiple apps. To promote discussion and present our future work, we introduce a mobile app that exploits the proposed methodology to assist users in monitoring and changing their smartphone habits through implementation intentions, i.e., "if-then" plans where if's are contextual cues and then's are goal-related behaviors.

Towards Detecting and Mitigating Smartphone Habits / MONGE ROFFARELLO, Alberto; DE RUSSIS, Luigi. - ELETTRONICO. - (2019), pp. 149-152. (Intervento presentato al convegno The 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) tenutosi a London (UK) nel 10-14 September, 2019) [10.1145/3341162.3343770].

Towards Detecting and Mitigating Smartphone Habits

Alberto Monge Roffarello;Luigi De Russis
2019

Abstract

Smartphones have the potential to produce new habits, i.e., habitual phone usage sessions consistently associated with explicit contextual cues. Despite there is evidence that habitual smartphone use is perceived as meaningless and addictive, little is known about what such habits are, how they can be detected, and how their disruptive effect can be mitigated. In this paper, we propose a data analytic methodology based on association rule mining to automatically discover smartphone habits from smartphone usage data. By assessing the methodology with more than 130,000 smartphone sessions collected in-the-wild, we show evidence that smartphone use can be characterized by different types of complex habits, which are highly diversified across users and involve multiple apps. To promote discussion and present our future work, we introduce a mobile app that exploits the proposed methodology to assist users in monitoring and changing their smartphone habits through implementation intentions, i.e., "if-then" plans where if's are contextual cues and then's are goal-related behaviors.
2019
978-1-4503-6869-8
File in questo prodotto:
File Dimensione Formato  
smartphonehabits.pdf

accesso aperto

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 777.22 kB
Formato Adobe PDF
777.22 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2740100
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo