My research lies at the intersection of machine learning and quantitative marketing. For example, I develop novel approaches to emotion detection and investigate emerging business models such as music streaming. Methodologically, I use machine learning techniques such as representation learning, causal inference, and traditional econometrics to analyze large-scale data. A recent example of my work is a Journal of Marketing publication on emoji-based emotion detection. In addition to my research, I serve as an ad-hoc reviewer for leading marketing journals, including the International Journal of Research in Marketing. I have also gained valuable international experience through research visits at Bocconi University (Milan), the University of New South Wales (Sydney), and the NYU Stern School of Business (New York).

Working papers

• The Impact of Social Media on Music Demand: Evidence from Quasi-Natural Experiments (with Daniel Winkler, Nils Wlömert, Dominik Papies, and Jūra Liaukonytė)
• The Decline of Superstars: Information Spillover Effects in the Streaming Age (with Nils Wlömert, and Eitan Muller)
• How Does a Product’s Recall Impact Its Retailer-Set Price? (with Marton Varga, Vivek Astvanash, and Abishek Borah)
• Privacy Regulations and Advertising in Offline Markets - Evidence from Randomized Field Experiments (with Alexandra Becker, Nils Wlömert, and Dominik Papies)
• The Personal Side of Human Brands: How Human Brand Messages on Social Media Drive Brand Consumption and Engagement (with Daniel Winkler, Nils Wlömert, and Harald Van Heerde)
• Effects of Rejected Upgrading Calls on Donor Behavior: A Study in Charitable Organizations (with Pascal Güntürkün, and Sven Mikolon)
• Learning from User-Product Interactions: A Representation Learning Approach (with Qiaoni Shi, and Kai Zhu)

Publications & proceedings

• 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. 55th Annual Hawaii International Conference on System Sciences, 2022. Proceedings of the (pp. 9–pp). IEEE. PDF
• 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. PDF

Presentations & invited talks

2025

• UNSW Research Seminar, Sydney, Australia — February 2025

2024

• Bocconi Research Seminar, Milan, Italy — October 2024

2023

• Symposium on the Special Issue on Marketing Impact with Research-Driven Apps in the Journal of Marketing — November 2023
• 45th ISMS Marketing Science Conference, Miami, USA — June 2023
• 3rd Marketing Analytics Symposium (MASS), Sydney, Australia — July 2023

2022

• Economics of the Music Industry, Hamburg, Germany — December 2022
• Bocconi Research Camp, Varese, Italy — October 2022
• Marketing Research Seminar, University of New South Wales, Sydney, Australia — September 2022
• 2nd Marketing Analytics Symposium (MASS), Sydney, Australia — July 2022

2021

• 50th Conference of the European Marketing Academy (EMAC), virtual — May 2021

2020

• 1st Marketing Analytics Symposium (MASS), Sydney, Australia — July 2020
• 42nd ISMS Marketing Science Conference, virtual — June 2020

2019

• 49th Conference of the European Marketing Academy (EMAC), Hamburg, Germany — May 2019
• 40th ISMS Marketing Science Conference, Rome, Italy — June 2019

2018

• 49th Conference of the European Marketing Academy (EMAC), Schottland, United Kingdom — May 2018

2017

• 39th ISMS Marketing Science Conference, Los Angeles, USA — June 2017