👋 Welcome! My name is Nader Hotait.

👨‍💻 I am a sociologist and postdoctoral researcher at the German Center for Integration and Migration Research (DeZIM) and at the Berlin Institute for Integration and Migration Research (BIM) at Humboldt University of Berlin. At DeZIM, I work in the Consensus and Conflict department and in the National Discrimination and Racism Monitor (NaDiRa). At Humboldt University, I founded and direct the Digital Muslim Studies Lab.

📚 I received my PhD in Sociology and Data Science from the University of Mannheim’s Graduate School of Economic and Social Sciences in 2025, including a visiting research studentship at the Data Science Institute of the London School of Economics and Political Science. My dissertation on Muslim TikTok in Germany was nominated for the German Thesis Award 2026 (Deutscher Studienpreis) of the Körber Foundation. In 2026, I was an Internet and Society Fellow at the Alexander von Humboldt Institute for Internet and Society (HIIG) in the focus area “Democratic Change and Knowledge”.

🔬 My research asks how recommendation algorithms and AI systems shape political attitudes and religious life online. One line of work uses digital field experiments to test whether algorithmically curated feeds on TikTok and YouTube change opinions, trust in institutions, and openness to extremist messages. A second line studies how Muslims in Europe use social media to build visibility and community, and how anti-Muslim racism and extremist actors operate in the same digital spaces. Increasingly, I also look at large language models as new sources of religious and everyday guidance.

👨‍🏫 Check out my talks and blogposts for updates and empirical insights into my work. The latter is where you can find my code (sometimes).

📓 Current Projects

📺 Media Diets and Democratic Values (MEDIVA)

Together with colleagues at Princeton University, I lead MEDIVA, a project funded by the Humboldt-Princeton Strategic Partnership. In a naturalistic experiment on YouTube, we alter the recommendations participants receive and measure whether algorithmically curated media diets change their knowledge, attitudes, and democratic values. The project combines the experimental design with computational analysis of the content participants actually watched. We presented first results at the MEDIVA symposium in Berlin in 2026.

📱 Radicalization Potentials on TikTok (RaPoTik)

RaPoTik, which I led together with my colleagues Özgür Özvatan and Rami Ali, was funded by the Berlin State Commission against Violence. It asked how common radical content is among German Muslim TikTok users and what exposure to it does.

The project had three stages. A qualitative study of Muslim content creators mapped their ideological diversity, narratives, and language. Building on this, we used Natural Language Processing to measure the prevalence of radical content in TikTok user data. Finally, we ran Germany’s first digital field experiment on TikTok, in which participants were exposed to the identified content through the TikTok interface for two weeks before we measured their attitudes.

The findings are published in a BIM Research Report and in a chapter of The Routledge International Handbook on Social Exclusion and Radicalisation.

🔎 Earlier Work

Before RaPoTik, I was responsible for Module 1 of the BMBF-funded D:Islam project, where I used computational methods to collect and analyze large amounts of online data for radical material. At DeZIM, I have worked on responses to racial discrimination and, more recently, on how German media cover racism and racially motivated violence.

📝 Selected Publications

• Hotait, N. (2026). Anti-Muslim racism, TikTok, and radicalization. Findings from a digital field experiment with Muslim TikTok users in Germany. BIM Research Report.
• Hotait, N. (2025). Beyond the hijab. Performing religious identity on TikTok. Social Compass.
• Hotait, N. (2024). Exploring the Role of TikTok for Intersectionally Marginalized Groups. The Case of Muslim Female Content Creators in Germany. Frontiers in Political Science, 6, 1496833.
• Hotait, N. (2024). Exploring (Anti-)Radicalism on TikTok. German Islamic Content Creators between Advocacy and Activism. Religions, 15(10).

The full list is in my CV.

🧰 Methods

I work with digital experiments, computational methods, natural language processing, causal inference, and non-probability designs, and collect data through surveys, data donations, APIs, and web scraping. My analyses range from regression and clustering to automated text analysis and the use of LLMs for classifying large corpora.

Research on radicalization has also shown me the limits of these tools. Automated detection is often trusted too readily, and inferences get drawn where context matters most. Meaning, ambiguity, and irony in extremist or religious content often only become visible through close engagement with the actors and material. For this reason, qualitative inquiry remains a fixed part of my research designs.

🤝 Transfer and Consulting

I regularly share my findings with policymakers, prevention practitioners, and platforms. This includes exchanges with the Federal Ministry of the Interior, the interior ministries of several German states, the Federal Office for the Protection of the Constitution, prevention organizations such as Violence Prevention Network, BAG RelEx, and ufuq.de, and the policy and safety teams of TikTok and Meta. I also comment on radicalization, disinformation, and Muslim life in Germany for outlets such as ARD, tagesschau, Deutsche Welle, taz, and The Economist.

Beyond this, I take on commissioned studies and training material for civil society organizations, foundations, and public bodies, and build interactive data explorers with Shiny and Markdown. If you are interested in working together, write to me at my academic addresses (BIM, DeZIM) or my private email.