Ecological momentary assessments (EMAs) prompt users with a short questionnaire. One of the biggest challenges in such studies is the lack of adherence, i.e., users stop filling out the questionnaires. Being able to predict if a user will fill out a questionnaire could allow for specifically addressing those users, or for over-sampling populations at higher … Read more
How can mobile sensing, using the smartphone’s sensors for recording and storing data, help in personality science? Read our comprehensive book chapter on this topic. We cover an overview of related work and show the differences in researching personality traits vs. personality states with mobile sensing. We showcase a concrete mobile-sensing application and provide a … Read more
Today, I gave a presentation at an IEEE EMBS (Engineering in Medicine and Biology Society) event. My talk was about Predicting Adherence to Ecological Momentary Assessments, and I presented our findings about the predictability of users of a smartphone app filling out questionnaires. Based on smartphone sensor data, we utilized machine learning to try to … Read more
Next app prediction can help enhance user interface design, pre-loading of apps, and network optimizations. Prior work has explored this topic, utilizing multiple different approaches but challenges like the user cold-start problem, data sparsity, and privacy concerns related to contextual data like location histories, persist. The user cold-start problem occurs when a user has recently … Read more
My PhD thesis (full title: Integrating Psychoinformatics with Ubiquitous Social Networking: Advanced Mobile-Sensing Concepts and Applications) was published as a book with Springer. You can read a preview of the book here. You can buy from Springer directly, or get it via Amazon (for example, US, DE, JP).
We investigated associations between personality traits and smartphone usage in daily life. 526 participants (mean age 34.57 years, SD = 12.85, 21% female) used TYDR (Track Your Daily Routine) for 48 days, on average (SD = 63.2, range 2 to 304). The Big Five Inventory 2 (BFI-2) was used to measure personality traits (Extraversion, Agreeableness, … Read more
Expanding on our earlier work on privacy in mobile sensing/data collection apps, we evaluated the data we collected with TYDR. Our experimental evaluation based on the first two month of data collected with TYDR shows evidence that our users accept our proposed privacy model. Based on data about granting TYDR all or no Android system … Read more
We presented TYDR and our first research results based on the collected data at the Long Night of Science in Berlin (German: Lange Nacht der Wissenschaften). Many visitors from all walks of life were curious to learn more about the app and our results. Additionally, we presented IC4F (Industrial Communication for Factories). For a non-technical … Read more
I had the chance to present my work around TYDR and preliminary results from the data we are collecting at an event of Berlin Science Talk.
