Christian Hotz-Behofsits

Christian Hotz-Behofsits is an Assistant Professor (tenure-track) at WU Vienna. He completed his PhD at WU under the supervision of Nadia Abou Nabout and Eitan Muller, building on an earlier background as a software and information engineer that continues to shape his empirical work with large-scale data under limited computational resources.

His research sits at the intersection of quantitative marketing, information systems, and econometrics. He studies how digital platforms, music streaming services and social media in particular, reshape consumer behavior and markets, and he develops the measurement tools needed to study them. A first strand examines the digital music economy: whether attention on TikTok promotes or cannibalizes streaming, how a viral hit spills over onto other artists, and how social-media activity drives the brands consumers buy. A second strand develops measurement methods for marketing, including inferring emotional expression from text via emojis and representing consumers and products as vectors in a shared space to recover individual preferences. He also applies causal methods to classic questions in retailing and advertising, such as how a product recall moves a retailer's prices or how privacy regulation reshapes offline advertising.

Methodologically, he combines representation learning, causal inference, machine learning, and natural language processing with traditional econometric techniques, applied to large-scale structured and unstructured data. His work on emoji-based emotion detection is forthcoming at the Journal of Marketing.

He serves as an ad-hoc reviewer for leading marketing journals, including the International Journal of Research in Marketing, and has held research visits at Bocconi University (Milan), the University of New South Wales (Sydney), and NYU Stern School of Business (New York).

Selected publications

• Hotz-Behofsits, C., Wlömert, N., & Abou Nabout, N. (2025). Natural Affect Detection (NADE): Inferring emotional expression from text through emojis. Journal of Marketing (forthcoming).

• Hotz-Behofsits, C., Winkler, D., & Wlömert, N. (2022). Music Genres Reconsidered: Challenging Established Genres with a Data-driven Approach. Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS), IEEE.

• Hotz-Behofsits, C., Huber, F., & Zörner, T. O. (2018). Predicting cryptocurrencies using sparse non-Gaussian state space models. Journal of Forecasting, 37(6), 627–640.

Selected working papers

• Does TikTok Promote or Cannibalize Music Streaming? Estimands and Identification with Heavy-Tailed Outcomes (with D. Winkler, N. Wlömert, D. Papies & J. Liaukonytė).

• When Hits Hurt: Cross-Artist Spillovers and the Attention Economy in Streaming Music (with N. Wlömert & E. Muller).

• The (Un)Professional Side of Human Brands: How Social Media Drives Brand Consumption (with D. Winkler, N. Wlömert & H. Van Heerde).

• Quantifying Consumer-Product Fit: A Representation Learning Approach (with Q. Shi, K. Zhu & A. Cao).

• How Does a Product's Recall Impact Its Retailer-Set Price? (with M. Varga, V. Astvansh & A. Borah).

• Privacy Regulations and Advertising in Offline Markets: Evidence from Randomized Field Experiments (with A. Becker, N. Wlömert & D. Papies).

Teaching

Christian teaches quantitative marketing, social media analytics, and data analysis at the undergraduate, master's, and executive level. Beyond WU Vienna he has taught at the University of Salzburg and internationally at the University of New South Wales (Australia), Thammasat Business School (Thailand), the University of Economics HCMC (Vietnam), and Gadjah Mada University (Indonesia).