MobRec – Mobile Platform for Decentralized Recommender Systems

Imagine getting recommendations, for example, for music or TV shows, based on similar people you pass by on the street. No server backend needed, all via device-to-device communication. We designed and implemented such a system. You can find our full article published in IEEE Access here (PDF) and the code on GitHub. We build the … Read more

What data are smartphone users willing to share with researchers?

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

Context Data Categories and Privacy Model for Mobile Data Collection Apps

Context-aware applications stemming from diverse fields like mobile health, recommender systems, and mobile commerce potentially benefit from knowing aspects of the user’s personality. As filling out personality questionnaires is tedious, we propose the prediction of the user’s personality from smartphone sensor and usage data. In order to collect data for researching the relationship between smartphone … Read more

Do You Like What I Like? Similarity Estimation in Proximity-based Mobile Social Networks

While existing social networking services tend to connect people who know each other, people show a desire to also connect to yet unknown people in physical proximity. Existing research shows that people tend to connect to similar people. Utilizing technology in order to stimulate human interaction between strangers, we consider the scenario of two strangers … Read more

TYDR – Track Your Daily Routine. Android App for Tracking Smartphone Sensor and Usage Data

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

Towards Psychometrics-based Friend Recommendations in Social Networking Services

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

Privacy-aware Social Music Playlist Generation

Listen to the music according to the taste of the people around you! We developed a system and implemented a mobile Android prototype and server system. We presented this work as a paper at the IEEE ICC 2016. You can find the full paper here (PDF). Two of the most popular applications of smartphones are … Read more

Project DYNAMIC started

Today officially starts my project DYNAMIC, for which I acquired funding at the competitive Software Campus program (funded through the Federal Ministry of Education and Research (BMBF)). DYNAMIC deals with distributed online social networks and with the creation of dynamic social graphs based on location, context, and profile data. In current Online Social Networks, relations … Read more

Towards a Three-tiered Social Graph in Decentralized Online Social Networks

We developed an approach and a software architecture for decentralized social networking services, focusing on the central role of the smartphone. We presented this work as a paper at the HotPOST 2015 workshop (co-located with ACM MobiHoc 2015) and received the Best Paper Runner-Up award! You can find the full paper here (PDF). Online Social … Read more