👋 Welcome! My name is Nader Hotait.

👨‍💻 I am research associate at the Berlin Institut for Integration and Migration Research (BIM) at the Humboldt University of Berlin and Lead Data Scientist at Transformakes.

📚 Also, I am a Ph.D. candidate in Sociology at the University of Mannheim’s Graduate School of Economic and Social Sciences and visiting researcher at the Data Science Institute of the London School of Econonomics and Political Science.

🔬 My current research encompasses two primary areas. First, I focus on radical material in algorithmically curated social media feeds and its effects on radicalization. Second, I investigate Muslim and Migrant communities online, assessing their impact on real-life politics, alongside founding and directing the Digital Muslim Studies Lab (DMS).

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

📓 Current Topics

📱 Radicalization Potentials on TikTok (RaPoTik)

I am leading a research project called RaPoTik (Radicalization Potentials on TikTok), in collaboration with my colleagues Özgür Özvatan and Rami Ali. This project is funded by the Berlin State Commission against Violence and aims to assess the threat of radicalization through TikTok consumption. TikTok has been under increasing scrutiny for disseminating extremist content, raising concerns about its impact on radicalization. Therefore, with RaPoTik, our primary objective is to investigate the prevalence of radical content among German Muslim TikTok users and evaluate the potential effects of this exposure on the process of radicalization.

Our research project consists of three key stages (see Figure below). The first stage involves conducting a qualitative inquiry of Muslim content creators on TikTok. This stage allows us to explore their ideological diversity, distinct narratives, and linguistic expressions. Not only do we intend to contribute to the broader study of Muslim communities but we also gather the necessary (prior) knowledge for the subsequent stages, as they are quantitative.

In the second stage, we employ Natural Language Processing (NLP) techniques to analyze TikTok user data, specifically to identify radical content. Our goal is to quantify the prevalence of radical content among German Muslim TikTok users. By leveraging computational methods, we can gain insights into the nature and pervasiveness of radical content on the platform.

The third stage of RaPoTik involves an experimental setting, where we deliberately expose participants to the identified radical content through the TikTok interface for two weeks. By measuring their responses and reactions afterward, we aim to understand the potential impact of exposure to such content. This stage allows us to examine the relationship between TikTok consumption, exposure to radical content, and potential radicalization tendencies.

🔎 Other Topics

I have experience in quantitative and qualitative research endeavors alike and managed different research projects throughout my career. My work spans various topics, including digitalization, social media studies, migration, radicalization, cultural studies, religion, race and migration, political sociology, and social inequality and stratification.

Right before RaPoTik, I was actively involved in the D:Islam project. Here, I held the responsibility for Module 1. In this role, I applied computational methods to access large data sources and analyzed them in terms of radical material. I also employed mixed-method approaches to gain further insights.

Methodologically, I engage with computational methods, natural language processing, causal inference, and non-probability sampling. In my research, I employ diverse data collection channels, including surveys, experiments, API access, and web scraping. When it comes to analysis, I’m rather eclectic. Although I am very fond of computational text analysis, my foundation lies in various regression and clustering techniques. However, when engaging with radicalization, the limits of computational and further quantitative methods have become all the more visible - at least it was so for me. Recent developments in detection methods and predictive analysis in criminological research are not without problems. Automated methods are often trusted blindly, leading to inferences made where context is highly needed. Setting aside the blatant biases in predictive policing. Profound levels of meaning, context, and ambiguity can only be accessed through immersion in the corresponding actors, materials, and domains, which is facilitated through qualitative inquiry. Hence, I believe that qualitative approaches are highly necessary and inform my research, especially when it comes to studying radicalization.

In addition to my research and academic pursuits, I actively engage in continuous communication and collaboration with practitioners in the field of prevention work and social media representatives. This ongoing exchange enables me to stay informed about current challenges in these areas. Furthermore, through my academic work, I strive to actively contribute to the field of prevention, providing insights on how to address emerging digital platforms or model algorithms to enhance safety.

For more detailed information about my experience and activities, feel free to download my CV.

📈 Freelance Services

I offer freelance services in the field of data science, with a focus on ESG (Environmental, Social, and Governance) and DEI (Diversity, Equity, and Inclusion) indicators. I provide research expertise to companies seeking to measure and assess specific ESG/DEI metrics. I do so through various methods such as surveys, interviews, and more. As an empirical social scientist, I leverage a strong theoretical foundation and utilize up-to-date operationalizations from the domain of (critical) social studies. This unique approach empowers me to deliver a substantial understanding of social data, transcending the boundaries of pure statistics or computer science.

Moreover, I specialize in constructing data dissemination tools through Shiny Apps and Markdown. These tools enable me to create interactive data explorers and reports, offering companies a user-friendly and engaging way to explore and understand their data. Should you be interested in my services, feel free to email me at my academic email addresses (Berlin, Mannheim) or simply use my private email.