Spotted: Using smartphones to sense too much smartphone use

But what do you do when you sense it's too much? We hate technology that nags. 
 
// published on Ubiquitous Computing-Latest Proceeding Volume // visit site

Automatically detecting problematic use of smartphones
Choonsung Shin, Anind K. Dey

Smartphone adoption has increased significantly and, with the increase in smartphone capabilities, this means that users can access the Internet, communicate, and entertain themselves anywhere and anytime. However, there is growing evidence of problematic use of smartphones that impacts both social and heath aspects of users' lives. Currently, assessment of overuse or problematic use depends on one-time, self-reported behavioral information about phone use. Due to the known issues with self-reports in such types of assessments, we explore an automated, objective and repeatable approach for assessing problematic usage. We collect a wide range of phone usage data from smartphones, identify a number of usage features that are relevant to this assessment, and build detection models based on Adaboost with machine learning algorithms automatically detecting problematic use.

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Spotted: App stores as a source of data for analytics data


 
// published on Human Computer Interaction with Mobile Devices and Services-Latest Proceeding Volume // visit site

Informing future design via large-scale research methods and big data
Mattias Rost, Alistair Morrison, Henriette Cramer, Frank Bentley

With the launch of 'app stores' on several mobile platforms and the great uptake of smartphones among the general population, researchers have begun utilising these distribution channels to deploy research software to large numbers of users. Previous Research In The Large workshops have sought to establish base-line practice in this area. We have seen the use of app stores as being successful as a methodology for gathering large amounts of data, leading to design implications, but we have yet to explore the full potential for this data's use and interpretation. How is it possible to leverage the practices of large-scale research, beyond the current approaches, to more directly inform future designs?

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Spotted: Contextualise! personalise! persuade!: a mobile HCI framework for behaviour change support systems


 // published on Human Computer Interaction with Mobile Devices and Services-Proceeding Volume // visit site

Contextualise! personalise! persuade!: a mobile HCI framework for behaviour change support systems

Sebastian Prost, Johann Schrammel, Kathrin Röderer, Manfred Tscheligi

This paper presents a context-aware, personalised, persuasive (CPP) system design framework applicable to the sustainable transport field and other behaviour change support system domains. It operates on a situational, a user, and a target behaviour layer. Emphasis is placed on interlinking each layer's behaviour change factors for greater effectiveness. A prototype CPP system for more sustainable travel behaviour is introduced to demonstrate how the framework can be applied in practice.

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