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Sensor data collected from smartphones provides the possibility to passively infer a user's personality traits. Such models can be used to enable technology personalization, while contributing to our substantive understanding of how human…
The exponential growth in smartphone adoption is contributing to the availability of vast amounts of human behavioral data. This data enables the development of increasingly accurate data-driven user models that facilitate the delivery of…
This study provides evidence that personality can be reliably predicted from activity data collected through mobile phone sensors. Employing a set of well informed indicators calculable from accelerometer records and movement patterns, we…
Large-scale collection of human behavioral data by companies raises serious privacy concerns. We show that behavior captured in the form of application usage data collected from smartphones is highly unique even in very large datasets…
Basic personality traits are typically assessed through questionnaires. Here we consider phone-based metrics as a way to asses personality traits. We use data from smartphones with custom data-collection software distributed to 730…
With the increasing usage of smartphones, there is a corresponding increase in the phone metadata generated by individuals using these devices. Managing the privacy of personal information on these devices can be a complex task. Recent…
Mobile phone metadata is increasingly used for humanitarian purposes in developing countries as traditional data is scarce. Basic demographic information is however often absent from mobile phone datasets, limiting the operational impact of…
Privacy personas capture the differences in user segments with respect to one's knowledge, behavioural patterns, level of self-efficacy, and perception of the importance of privacy protection. Modelling these differences is essential for…
Data minimisation is a privacy-enhancing principle considered as one of the pillars of personal data regulations. This principle dictates that personal data collected should be no more than necessary for the specific purpose consented by…
With the growing amount of personal information exchanged over the Internet, privacy is becoming more and more a concern for users. One of the key principles in protecting privacy is data minimisation. This principle requires that only the…
Mobile phone data -- with file sizes scaling into terabytes -- easily overwhelm the computational capacity available to some researchers. Moreover, for ethical reasons, data access is often granted only to particular subsets, restricting…
Personal data cover multiple aspects of our daily life and activities, including health, finance, social, Internet, Etc. Personal data visualisations aim to improve the user experience when exploring these large amounts of personal data and…
A number of learning models used in consequential domains, such as to assist in legal, banking, hiring, and healthcare decisions, make use of potentially sensitive users' information to carry out inference. Further, the complete set of…
Previous studies have shown the correlation between sensor data collected from mobile phones and human depression states. Compared to the traditional self-assessment questionnaires, the passive data collected from mobile phones is easier to…
Sharing location traces with context-aware service providers has privacy implications. Location-privacy preserving mechanisms, such as obfuscation, anonymization and cryptographic primitives, have been shown to have impractical…
Not all smartphone owners use their device in the same way. In this work, we uncover broad, latent patterns of mobile phone use behavior. We conducted a study where, via a dedicated logging app, we collected daily mobile phone activity data…
Recommender Systems have not been explored to a great extent for improving health and subjective wellbeing. Recent advances in mobile technologies and user modelling present the opportunity for delivering such systems, however the key issue…
In domains with high stakes such as law, recruitment, and healthcare, learning models frequently rely on sensitive user data for inference, necessitating the complete set of features. This not only poses significant privacy risks for…
Personality profiling has been utilised by companies for targeted advertising, political campaigns and public health campaigns. However, the accuracy and versatility of such models remains relatively unknown. Here we explore the extent to…
Loneliness is a critical mental health issue among university students, yet traditional monitoring methods rely primarily on retrospective self-reports and often lack real-time behavioral context. This study explores the use of passive…