Kilian Theil


B6, 26, Room C1.05

E-mail: kilian (at)

Focus group: Artificial intelligence

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Research Interests

  • Natural Language Processing in behavioral economics
    • Linguistic uncertainty detection in financial disclosures
    • Risk explanation/prediction from text
  • Ethical implications of smart cities
    • Agent-based traffic simulations

Working Papers

  • Theil, Kilian; Hovy, Dirk; Stuckenschmidt, Heiner: “Top-Down Influence? Predicting CEO Personality and Risk Impact from Speech Transcripts.” arXiv link.
  • Theil, Kilian; Daube, Jens; Stuckenschmidt, Heiner: “Causal Effects of Linguistic Uncertainty on Risk Perception and Investment Behavior.” SSRN link.


  • Kappenberger, J., Theil, K. and Stuckenschmidt, H. (2022). Evaluating the impact of AI-based priced parking with social simulation. In , Social Informatics: 13th International Conference, SocInfo 2022, Glasgow, UK, October 19–21, 2022, proceedings (S. 54–75). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
  • Theil, C. K. and Stuckenschmidt, H. (2020). Predicting modality in financial dialogue. In , FNP-FNS 2020 : Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation, December 2020, Barcelona, Spain (Online) (S. 226–234). ACL Anthology, Association for Computational Linguistics: Stroudsburg, PA.
  • Theil, C. K., Broscheit, S. and Stuckenschmidt, H. (2019). PRoFET: Predicting the risk of firms from event transcripts. In , Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10–16, 2019 (S. 5211–5217). , IJCAI/AAAI Press: Menlo Park, CA.
  • Theil, C. K., Štajner, S. and Stuckenschmidt, H. (2018). Word embeddings-based uncertainty detection in financial disclosures. In , Economics and Natural Language Processing – proceedings of the First workshop (ECONLP 2018) : July 20, 2018, Melbourne, Australia : ACL 2018 (S. 32–37). , Association for Computational Linguistics: Stroudsburg, PA.
  • Theil, C. K., Štajner, S., Stuckenschmidt, H. and Ponzetto, S. P. (2018). Automatic detection of uncertain statements in the financial domain. In , Computational Linguistics and Intelligent Text Processing : 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II (S. 642–654). Lecture Notes in Computer Science, Springer: Berlin [u.a.].

Review Activities



  • Jonathan Baumert (2022, M.Sc.): Measuring Corporate Alignment with the Sustainable Development Goals
  • Jakob Gutmann (2021, M.Sc.): Modelling Dynamic Pricing Schemes for Parking in Inner Cities
  • Paul Exner (2021, B.Sc.): Simulating Socio-Economic Effects of Parking Violation Detection
  • Jens Daube (2020, M.Sc.): Experimental Evaluation of Uncertainty Perception in Financial Disclosures
  • Eni Papuciu (2019, M.Sc.): Detecting Linguistic Uncertainty in Finance and Measuring Its Perception

Supplementary Material

  • Code and data of our 2020 COLING FNP paper “Predicting Modality in Financial Dialogue”
  • Code and data of our 2020 ACM-TDS paper “Explaining Financial Uncertainty Through Specialized Word Embeddings”
  • Code, data and embedding models of our 2019 IJCAI paper “PRoFET: Predicting the Risk of Firms from Event Transcripts”
  • Appendix and embedding model of our 2018 ACL ECONLP paper “Word Embeddings-Based Uncertainty Detection in Financial Disclosures”
  • Dataset of our 2017 CICLing paper; sentences and labels (“c” = certain, “u” = uncertain) are comma-separated