Publications on
Predictive Psychometrics

Matz, S. C., Bukow, C. S., Peter, H., Dinu, A., Deacons, C. & Stachl, C. (2023). Throwing the cap or throwing in the towel? Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics. Scientific Reports

Ramon*+, Y., Matz, S. C., Farrokhnia, R. A. & Martens, D. (2022). Explainable AI for Psychological Profiling from Digital Footprints: A Case Study of Big Five Personality Predictions from Spending Data. Information.

Giorgi, S., Lynn, V., Gupta, K., Ahmed, F., Matz, S. C., Ungar, L., Schwartz, H. A. (2022). Correcting sociodemographic selection bias for population prediction from social media. ICWSM '22

Stachl, C., Boyd, R. L., Horstman, K.T, Khambatta, P. Matz, S. C., & Harari, G. M. (2021). Computational personality assessment. Personality Science, 2, 1-22.

Tovanich, N., Centellegher, S., Seghouani, N. B., Gladstone, J., Matz, S. C, & Lepri, B. (2021). Inferring psychological traits from spending categories and dynamic consumption patterns. EPJ Data Science, 10(1), 1-23.

Hall, A+. & Matz, S. C. (2020). Targeting Item-Level Nuances Leads to Small but Robust Improvements in Personality Prediction from Digital Footprints. European Journal of Personality.

Matz, S. C., Menges, J. I., Stillwell, D. J. & Schwartz, H. A. (2019). Income is predictable from Facebook profiles. PLoSONE

Gladstone, J. J.*, & Matz, S. C.*, Lemaire, A. (2019). Can Psychological Traits be Inferred from Spending: Evidence from Transaction Data. Psychological Science, 30(7):1087-1096.

Kulkarni+, V., Kern M. L., Stillwell, D., Kosinski, M., Matz, S. C., Ungar, L., Skiena, S. & Schwartz, A.  (2018). Latent Human Traits in the Language of Social Media: An Open-Vocabulary Approach. PLoSONE