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 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
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
Expanding our earlier work on choice overload in related-article recommendations, we analyzed a digital library to figure out the ideal number of recommendations to show to users. Some of our metrics point toward 5-6 items as the ideal number of recommendations to display. You can find the full paper here (PDF). Choice Overload describes a … Read more
We present the Android app TYDR (Track Your Daily Routine) which tracks smartphone sensor and usage data and utilizes standardized psychometric personality questionnaires. With the app, we aim at collecting data for researching correlations between the tracked smartphone data and the user’s personality in order to predict personality from smartphone data. We highlight our approaches … Read more
Two of the defining elements of Social Networking Services are the social profile, containing information about the user, and the social graph, containing information about the connections between users. Social Networking Services are used to connect to known people as well as to discover new contacts. Current friend recommendation mechanisms typically utilize the social graph. … Read more
We investigate the problem of choice overload – the difficulty of making a decision when faced with many options – when displaying related-article recommendations in digital libraries. So far, research regarding to how many items should be displayed has mostly been done in the fields of media recommendations and search engines. We analyze the number … Read more
