My primary research focus is basic research on person-environment interactions in online contexts. I explore how different technologies change how information is created, distributed, filtered, organized, and finally presented to individuals online. Moreover, I am interested in how individuals with different characteristics co-produce and cognitively process this information and, building on that, form and change their political views and behaviors. As such, I examine if/how technologies – like recommender algorithms and (generative) AI – contribute to the emergence of online phenomena known as “filter bubbles” or “echo chambers” and mis-/disinformation. Furthermore, I investigate psychological characteristics that make individuals more or less susceptible to them. This includes personality traits, cognitive characteristics, and prior views. Additionally, I am interested in how online phenomena may impact the cognitive processing of information in different individuals – e.g., reflexive versus reflective and politically motivated versus accuracy-oriented reasoning as well as cognitive biases. Finally, how this impacts the formation of political views and may, for example, contribute to political polarization is part of my research. Beyond that, I investigate how different technologies (de-)motivate individuals to politically participate or act in line with their political views.
Building on my basic research, I strive to also conduct applied research: Here, I aim to contribute to the development of empirically validated measures to support (vulnerable) individuals in forming informed and – as far as possible – unbiased views in the online world and acting upon them. Such measures include (i) recommendations on how to modify existing online technologies and platforms, (ii) developing and validating novel online technologies and platforms, and (iii) training interventions supporting individuals in navigating the existing online world. These measures aim to reduce risks like polarization and strengthen political participation.
To address these research foci in a rigorous way, I also work on overcoming methodological challenges. These challenges concern the clear definition, conceptualization, and reliable and valid assessment of political individual differences variables, like ideology, political orientation, and support for democracy. Another challenge is distinguishing such concepts and understanding their nomological networks.
To investigate the topics mentioned, I adopt a multi-methodological, inter- and transdisciplinary research approach. I collaborate with experts from psychology, political, media and communication, as well as computer sciences from academia and industry to integrate diverse theories and methods. Regarding methods, I use (online) experiments, surveys, and tests. Additionally, I combine data from these research designs with digital trace data for high ecological validity. Furthermore, I have published literature reviews and meta-analyses, and I develop measurement instruments, as continuous and quick developments in my research field often demand the development of novel measures and operationalizations. Concerning statistics, I apply predictive modeling and machine learning techniques as well as other computational models next to descriptive and inferential statistics, underscoring my expertise in advanced statistical methods.
Finally, open science and good scientific practice are extremely important to me, and I adhere to the respective standards in all my projects (OSF profile: https://osf.io/xt7pn/#!).