Notifications are one of the most essential features of smartphones. App developers and researchers typically want to reach their audience at opportune times. We analyzed almost 10 million notifications collected from 922 users. Most notifications were logged in the late morning and late afternoon. Between 8 pm and 11 pm, the interaction delay (time between … Read more
Vision Transformers can outperform other methods like RNNs in classification tasks in the medical domain. MedMNIST (v2) is a collection of biomedical images, and contains eight 2D image datasets for a multi-class classification task. Using a pre-trained Vision Transformer model, and fine-tuning it for each dataset, we were able to outperform almost all of the … Read more
The COVID-19 pandemic not only affected the respiratory system, but, together with measures like social distancing, potentially affected the mental health of millions of people. What do Twitter (X) users talk about when they talk about #MentalHealth and #Depression? Did it change through the pandemic? We collected almost 3,000,000 tweets from more than 300,000 Twitter … Read more
How well can we detect stress from sensor data from wearables? And how to develop systems for it fast? You can find the full project and code on GitHub and a paper here (PDF). Or just visit the interactive live demo showcasing the whole project right now!
With about 300 million affected people, major depressive disorder (MDD) is one of the most common diseases worldwide. During the COVID-19 pandemic, the number of cases increased even further, by 28%. Many factors may be correlated with MDD, including the excessive use of social media apps. We investigated the relationship between the use of social … Read more
Can you predict if a self-described pornography-addict will relapse – based on his previous mental condition? We used machine learning to answer this question based on data collected by polish collaborators. Users used a mobile app for tracking their addictions and mental state. You can find a full project description and code on GitHub.
Today, I am starting at the National Institute of Informatics (NII) in the group of Prof. Akiko Aizawa. I acquired funding financing my full-time position in the competitive program IFI (German: Internationale Forschungsaufenthalte für Informatikerinnen & Informatiker) by the German Academic Exchange Service (DAAD). I will work on topics relating to user retention, data science, … 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
Several governments introduced or promoted the use of contact-tracing apps during the ongoing COVID-19 pandemic. In Germany, the related app is called Corona-Warn-App, and by end of 2020, it had 22.8 million downloads. Contact tracing is a promising approach for containing the spread of the novel coronavirus. It is only effective if there is a … Read more
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
