Smartphone usage in the wild: a large-scale analysis of applications and context

This paper presents a large-scale analysis of contextualized smartphone usage in real life. We introduce two contextual variables that condition the use of smartphone applications, namely places and social context. Our study shows strong dependencies between phone usage and the two contextual cues, which are automatically extracted based on multiple built-in sensors available on the phone. By analyzing continuous data collected on a set of 77 participants from a European country over 9 months of actual usage, our framework automatically reveals key patterns of phone application usage that would traditionally be obtained through manual logging or questionnaire. Our findings contribute to the large-scale understanding of applications and context, bringing out design implications for interfaces on smartphones.

[1]  Louise Barkhuus,et al.  Empowerment through seamfulness: smart phones in everyday life , 2011, Personal and Ubiquitous Computing.

[2]  Mika Raento,et al.  Smartphones , 2009 .

[3]  Jan Blom,et al.  Contextual and cultural challenges for user mobility research , 2005, CACM.

[4]  David Lazer,et al.  Inferring friendship network structure by using mobile phone data , 2009, Proceedings of the National Academy of Sciences.

[5]  Alex S. Taylor,et al.  The Gift of the Gab?: A Design Oriented Sociology of Young People's Use of Mobiles , 2003, Computer Supported Cooperative Work (CSCW).

[6]  D. Lazer,et al.  Inferring Social Network Structure using Mobile Phone Data , 2006 .

[7]  Daniel Gatica-Perez,et al.  Discovering human places of interest from multimodal mobile phone data , 2010, MUM.

[8]  Donna J. Reid,et al.  THE SOCIAL AND PSYCHOLOGICAL EFFECTS OF SMS TEXT MESSAGING , 2004 .

[9]  Rebecca E. Grinter,et al.  Wan2tlk?: everyday text messaging , 2003, CHI '03.

[10]  Yi Wang,et al.  A framework of energy efficient mobile sensing for automatic user state recognition , 2009, MobiSys '09.

[11]  A. Pentland,et al.  Eigenbehaviors: identifying structure in routine , 2009, Behavioral Ecology and Sociobiology.

[12]  Hannu Verkasalo,et al.  Handset-based analysis of mobile service usage , 2009 .

[13]  Mika Raento,et al.  Interpreting and Acting on Mobile Awareness Cues , 2007, Hum. Comput. Interact..

[14]  D. Gática-Pérez,et al.  Towards rich mobile phone datasets: Lausanne data collection campaign , 2010 .

[15]  Timothy Sohn,et al.  A large scale study of text-messaging use , 2010, Mobile HCI.

[16]  Ken Anderson,et al.  Numbers Have Qualities Too: Experiences with Ethno‐Mining , 2009 .

[17]  Deborah Estrin,et al.  Diversity in smartphone usage , 2010, MobiSys '10.

[18]  Rebecca E. Grinter,et al.  Y Do Tngrs Luv 2 Txt Msg? , 2001, ECSCW.

[19]  J. Donner Microentrepreneurs and Mobiles: An Exploration of the Uses of Mobile Phones by Small Business Owners in Rwanda , 2004 .

[20]  James G. Phillips,et al.  Personality and self reported mobile phone use , 2008, Comput. Hum. Behav..

[21]  Daniel Gatica-Perez,et al.  By their apps you shall understand them: mining large-scale patterns of mobile phone usage , 2010, MUM.

[22]  Mika Raento,et al.  ContextPhone: a prototyping platform for context-aware mobile applications , 2005, IEEE Pervasive Computing.

[23]  C.Y. Wei,et al.  Capturing Mobile Phone Usage: Research Methods for Mobile Studies , 2007, 2007 IEEE International Professional Communication Conference.