Jan Blom

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.

Personalization: a taxonomy

Personalization is here defined as a process of changing a system to increase its personal relevance. This may have a work or social motivation. A taxonomy of motivations is developed and illustrated by application to mobile phones and e-commerce Web pages.

Who's Who with Big-Five: Analyzing and Classifying Personality Traits with Smartphones

In this paper, we investigate the relationship between behavioral characteristics derived from rich smart phone data and self-reported personality traits. Our data stems from smart phones of a set of 83 individuals collected over a continuous period of 8 months. From the analysis, we show that aggregated features obtained from smart phone usage data can be indicators of the Big-Five personality traits. Additionally, we develop an automatic method to infer the personality type of a user based on cell phone usage using supervised learning. We show that our method performs significantly above chance and up to 75.9% accuracy. To our knowledge, this constitutes the first study on the analysis and classification of personality traits using smartphone data.

Contextual and cultural challenges for user mobility research

Personal, mobile synchronous and asynchronous communication has proven to be very desirable for all types of users, with estimates of more than a half-billion mobile phones sold each year [2]. Nokia Research Centers User Experience Group, working with other user practitioners in Nokia, seeks to understand why people do the things they do with their mobile communication devices and proposes solutions that best address their wants and needs. In accordance with the principles of user-centric product concept design [4], the solutions are designed to inform and inspire the product creation process within Nokia. Given that the group works three to eight years ahead of what appears on the market, confidentiality concerns restrict disclosure of many of these concepts and the findings on which these concepts are based. Instead, in this article we share some of the essential lessons learned from our projects centering on the early stages of product concept development. Two areas have proved to be particularly challenging in this respect: coping with multiple contexts and multiple cultures in the study of mobility.

Discovering places of interest in everyday life from smartphone data

In this paper, a new framework to discover places-of-interest from multimodal mobile phone data is presented. Mobile phones have been used as sensors to obtain location information from users’ real lives. A place-of-interest is defined as a location where the user usually goes and stays for a while. Two levels of clustering are used to obtain places of interest. First, user location points are grouped using a time-based clustering technique which discovers stay points while dealing with missing location data. The second level performs clustering on the stay points to obtain stay regions. A grid-based clustering algorithm has been used for this purpose. To obtain more user location points, a client-server system has been installed on the mobile phones, which is able to obtain location information by integrating GPS, Wifi, GSM and accelerometer sensors, among others. An extensive set of experiments has been performed to show the benefits of using the proposed framework, using data from the real life of a significant number of users over almost a year of natural phone usage.

InfoRadar: group and public messaging in the mobile context

Previous research has sought to utilize everyday messaging metaphors, such as the notice board, in location-based messaging systems. Unfortunately, many of the restrictions associated with the metaphors have been unnecessarily reintroduced to interaction, and results from the previous field trials have been disheartening. InfoRadar builds on experiences with these systems by presenting improvements in user interface functionality and services. By providing a novel radar interface for accessing messages, desktop-like temporal storage for messages, location-independent message threading, filtering functionality, contextual audience addressing, multimedia messaging, social activity indicator, and voting, InfoRadar attempts to combine both public and in-group messaging into one system. A preliminary field trial indicates that location-based aspects may have a role in facilitating mobile communication, particularly when it comes to engaging in social interaction with unknown people.

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

Fear and the city: role of mobile services in harnessing safety and security in urban use contexts

This paper describes investigation of a mobile communication system that helps alleviate fear experienced in the urban context. In order to obtain empirically grounded insights for the concept design, urban females in their twenties and thirties and living in Bangalore, New Delhi and San Francisco, were studied. More than 200 females filled in an online survey. Extensive qualitative data for 13 participants were collected through week long diaries, semi-structured interviews, and situated participative enactment of scenarios. Fear-related concerns were voiced both in India and the U.S., suggesting that reducing fear, particularly in a pedestrian context after the onset of darkness, could be a globally applicable need. User research findings into subjective experiences of fear, contexts in which they occur, and behavioral strategies were used to design a mobile service titled ComfortZones. This concept was developed to the level of a high fidelity prototype and tested in a field trial in India. The investigation highlights further opportunities for design, particularly the notion of emphasizing positive and socially successful qualities of cities to communities concerned with their safety and security.

Design of mobile wellness applications: identifying cross-cultural factors

This paper explores the design of mobile applications for supporting wellness activities. A cross-cultural user study was conducted in India and Finland. 16 participants used a technology probe (a mobile application called Wellness Diary) for the duration of two weeks. The focus of the study was to identify design factors that need to be considered when designing culturally sensitive mobile wellness applications. The findings are based on the subjective user experience reported by the participants, data collected with the technology probe, and ideas and needs of the participants that surfaced during the study. Results show that both cultural and environmental factors affect the needs towards the wellness application and usage of it. Differences were identified, for example, in how users defined wellness, what wellness concerns they had, attitudes towards setting goals, and how built and natural environments affected wellness activities.

A theory of personalisation of appearance: quantitative evaluation of qualitatively derived data

Using qualitative data, Blom and Monk (2003) derived a theory of why people choose to personalise the appearance of their PCs and mobile phones. This paper describes some quantitative data that provide some support for, and some modifications to, the theory. Individuals having personal home pages were recruited to fill in a questionnaire that assesses dispositions to personalise and its effects. In addition the 82 home pages were inspected to assess the extent of personalisation. This correlated significantly with the dispositions ‘Frequency of Use’ and ‘Knowledge of Personalisation’. The questionnaire items corresponding to effects were factor analysed. A four-factor solution suggested item groupings similar, but not identical, to those used in the theory. There are significant positive correlations between the extent of personalisation and cognitive effects and enduring emotional effects. The value of quantitative data for confirming and refining a qualitative theory is discussed.