Christoph Weisser

Bio and publications

Christoph joined the Chair of International Economic Policy and the Chair of Statistics as a doctoral student in 2019. He completed the PhD Programme in Applied Statistics and Empirical Methods. Christoph completed his PhD in May 2022.

He studied Economics at the University of Göttingen and completed two master degrees in Finance (MLitt) and Economic History (MSc) at the University of St. Andrews and the University of Oxford as a scholar of the Studienstiftung des deutschen Volkes. Subsequently, he worked in the financial industry in London.

Christoph is interested in the application of Machine Learning methods and in particular Natural Language Processing in Economics.

For his research on spatial statistics, please see also Mapping Coronavirus For China. Christoph is also leading a Natural Language Processing/Machine Learning project with the United Nations. Please get in touch if you are interested.

Publications can be found in Google Scholar


Working Paper

  • Buchmüller, A., Kant, G., Weisser, C., Kis-Katos, K., Säfken, B., Kneib T., Twitmo: A Twitter Data Topic Modeling and Visualization Package.
  • Thielman, A, Weisser, C., Kneib, T., Säfken, B., Coherence Based Clustering.
  • Luber, M., Weisser, C., Thielmann, A., B. Säfken, Community-Detection via Hashtag-Graphs for Semi-Supervised NMF Topic Models.
  • Stemmler, H., Kis-Katos, K., Lenel, F., Weisser, C., Dealing with agricultural shocks: Income source diversification through solar panel home systems.
  • Svanidze, D., Python, A., Weisser, C., Säfken, B., Kneib, T., Fine-Scale Spatial Predictions of COVID-19 Cases in China using GIS Data and Deep Learning Algorithms.
  • Dreher, A., Kis-Katos, K., Moellerherm, R., Weisser, C., Terrorism in the media.
  • Tillmann, A., Reinhardt, D., Kqiku, L., Weisser, C., Säfken, B., Kneib, T., What explains privacy on Twitter? Modelling the non-linear effect of latent topics on privacy by integrating XGBoost, Topic Models and Generalized Additive Models.
  • Alkhayer, T., Kivimaki, T., Kant, G., Weisser, C., Out-Groups and Threats as a Foundation for Terrorist Rhetoric: a Natural Language Processing based Sociopsychological Analysis of ISIS’s Al-Naba Magazine.


Machine Learning and Artificial Intelligence (Summer School, Studienstiftung des deutschen Volkes, University of Cambridge)
Deep Learning Algorithmen (Master, University of Göttingen)
Spatial Statistics (Master, University of Göttingen)