Syed Muhammad Usman Tayyab

My research interests lie at the intersection of corporate communication, digital activism, and the evolving landscape of public discourse. My research explores how corporations, alongside their leaders, navigate and influence sociopolitical issues through the strategic use of digital platforms, such as social media. I am also interested in exploring the impact of Generative AI on society, organizational practices, digital platforms, and online communities. I am keen on studying human-AI collaboration in various contexts. Moreover, I am intrigued by the interplay between traditional mass media and social media, examining how these platforms interact and influence each other in shaping public opinion and corporate behavior. Finally, I am particularly interested in the potential of digital trace data to address complex research questions, exploring novel ways to obtain and analyze this data. Additionally, I focus on the ethical considerations surrounding its use.

Methodologically, I specialize in a data-driven, computationally intensive grounded theory approach and algorithmic supported induction. In my research I mostly work with large-scale digital trace data. I adopt a mixed-methods strategy, integrating computational techniques like machine learning, natural language processing, and pattern recognition with traditional methods such as multiple-case studies analysis, econometric modeling, and SEM. Time series analysis and FsQCA are also key tools in my methodological repertoire.