Publications of Philipp Lorenz-Spreen

Borukhson, D., Lorenz-Spreen, P., & Ragni, M. (2022). When does an individual accept misinformation? An extended investigation through cognitive modeling. Computational Brain & Behavior, 5, 244–260. https://doi.org/10.1007/s42113-022-00136-3

Garrett, P. M., White, J. P., Dennis, S., Lewandowsky, S., Yang, C.-T., Okan, Y., Perfors, A., Little, D. R., Kozyreva, A., Lorenz-Spreen, P., Kusumi, T., & Kashima, Y. (2022). Papers please: Predictive factors of national and international attitudes toward immunity and vaccination passports. Online representative surveys. JMIR Public Health and Surveillance, 8(7), Article e32969. https://doi.org/10.2196/32969

Grüning, D. J., Panizza, F., & Lorenz-Spreen, P. (in press). The importance of informative interventions in a wicked environment. The American Journal of Psychology.

Lorenz-Spreen, P., Oswald, L., Lewandowsky, S., & Hertwig, R. (in press). Digital media and democracy: A systematic review of causal and correlational evidence worldwide. Nature Human Behaviour.

Baumann, F., Lorenz-Spreen, P., Sokolov, I. M., & Starnini, M. (2021). Emergence of polarized ideological opinions in multidimensional topic spaces. Physical Review X, 11, Article 011012. https://doi.org/10.1103/PhysRevX.11.011012

Kozyreva, A., Lorenz-Spreen, P., Hertwig, R., Lewandowsky, S., & Herzog, S. M. (2021). Public attitudes towards algorithmic personalization and use of personal data online: Evidence from Germany, Great Britain, and the United States. Humanities and Social Sciences Communications, 8, Article 117. https://doi.org/10.1057/s41599-021-00787-w

Kozyreva, A., Lorenz-Spreen, P., Lewandowsky, S., Garrett, P. M., Herzog, S. M., Pachur, T., & Hertwig, R. (2021). Psychological factors shaping public responses to COVID-19 digital contact tracing technologies in Germany. Scientific Reports, 11, Article 18716. https://doi.org/10.1038/s41598-021-98249-5

Lorenz-Spreen, P., Geers, M., Pachur, T., Hertwig, R., Lewandowsky, S., & Herzog, S. M. (2021). Boosting people’s ability to detect microtargeted advertising. Scientific Reports, 11, Article 15541. https://doi.org/10.1038/s41598-021-94796-z

Amazeen, M. A., Benevenuto, F., Brashier, N. M., Bond, R. M., Bozarth, L. C., Budak, C., Ecker, U. K. H., Fazio, L. K., Ferrara, E., Flanagin, A. J., Flammini, A., Freelon, D., Grinberg, N., Hertwig, R., Jamieson, K. H., Joseph, K., Jones, J. J., Garrett, R. K., Kreiss, D., McGregor, S., McNealy, J., Margolin, D., Marwick, A., Menczer, F., Metzger, M. J., Nah, S., Lewandowsky, S., Lorenz-Spreen, P., Ortellado, P., Pasquetto, I., Pennycook, G., Porter, E., Rand, D. G., Robertson, R., Swire-Thompson, B., Tripodi, F., Vosoughi, S., Vargo, C., Varol, O., Weeks, B. E., Wihbey, J., Wood, T. J., & Yang, K.-C. (2020). Tackling misinformation: What researchers could do with social media data. The Harvard Kennedy School Misinformation Review, 1(8). https://doi.org/10.37016/mr-2020-49

Baumann, F., Lorenz-Spreen, P., Sokolov, I. M., & Starnini, M. (2020). Modeling echo chambers and polarization dynamics in social networks. Physical Review Letters, 124(4), Article 048301. https://doi.org/10.1103/PhysRevLett.124.048301