Prediction of big five personality traits from mobile application usage

Abstract. Smartphones evolved being an integral part of our daily lives and in recent days. Studies show that smartphone usage is correlated to user personality traits. This critical ecosystem is dependent on several variables such as geographic location, demographic traits, ethnic impact or cultural influence and so on. While significant number of demographic, environmental and medical analysis is done based on smartphone usage, there are inadequate amount of study carried out to analyse human personality. All of these information provide pivotal insights for improving user experience, creating recommendations, identifying marketing strategies and for a general overall usage improvement. This study is done with application usage data collected over 6 months from 739 Android smartphone users along with a 50-item Big Five Personality Trait questionnaire. The analysis focuses on the fact that, category-level aggregated application usage is enough for predicting Big Five personality traits achieving 9–14% error which is 86–91% accuracy on average. This study concludes that user personality generates a fundamental impact on smartphone application and application category usage. This work reflects the possible personality-driven research in future and depicts the significance and involvement of application categories in achieving proper accuracy in general traits, while pursuing for personality study

Challenges on collecting smartphone data in cold environments

Abstract Smartphones can be considered the cheapest and well-penetrated devices for collecting everyday human behaviour data. However, smartphones, as any battery-dependant electronic devices, face a number of problems when exposed to below-freezing conditions, from sudden crashes and decreased battery life to challenging usage experiences such as freezing fingers especially during prolonged periods of time. In this paper, we present the results of a user survey (N=130, 59% female) exploring smartphone usage in below-freezing temperatures, including the problems caused by cold conditions and prevention mechanisms users could be willing to take to protect their device and user experience during winter months

Revitalizing Viena Karelian dialect and culture with gamification

Abstract Revitalizing Viena Karelian dialect by finding new ways of learning and teaching Karelian culture and language is important. Karelian is a Finnic language and it is the closest linguistic relative to Finnish. It is spoken in Finland and Russia and its dialects must not be mixed up with Karelian (south-eastern) dialects of Finnish. It is estimated that there are approximately 5,000 speakers of Karelian language in Finland and about 20,000 persons can understand it to some extent. According to the 2002 census, there are approximately 53,000 Karelian speakers in Russia. In both countries, speakers are mainly elderly. Therefore, the gamification approach was used to design and develop an educational game from non-gaming contexts for aiming to prevent language or its dialects extinction. In this study, a ”Let’s Learn Karelian” game prototype was designed for learning Viena Karelian dialect where English and Finnish users can use it and learn in a fun and effective way. A non functional prototype was developed with the Microsoft PowerPoint in a mobile context to get preliminary feedback from users. A relatively small user experience study with five participants was conducted in the early phase of development at the University of Oulu. Based on the feedback, the game prototype was perceived as visually pleasant, creative, easy to use, playful and entertaining. This paper also briefly introduces our new functional ”Learn Viena Karelian” prototype. According to our findings there is a need to develop various games for revitalizing Viena Karelian dialect and culture

The impact of smartphone usage on circadian cycles:a case study with wearable ring

Abstract Smartphones are an integral part of our daily life, bringing both positive and negative impacts with them. Recent studies suggest that extensive and untimely smartphone usage directly affects circadian rhythm, i.e. alertness-sleepiness cycle. In this paper, we analyse sleep quality data collected through a wearable ring together with the smartphone interaction in bed just before falling asleep. First, we show that the sleep-tracking devices measuring sleep quality and quantity are also feasible to be used for researching circadian cycles. Second, we analyse the statistical relationships between in-bed smartphone interaction and different sleep metrics, out of which some are more prominent for future use and some present interesting negative results. Third, we present three baseline prediction models to predict sleep quality and circadian cycle based on smartphone app usage, with accuracy ranging from 31% to 67%