Kilian Theil

Researcher

B6, 26, Room C1.05

E-mail: kilian (at) informatik.uni-mannheim.de

Focus group: Artificial intelligence

ORCID, Google Scholar, LinkedIn

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.].

Theil, C. K., Štajner, S. and Stuckenschmidt, H. (2020). Explaining financial uncertainty through specialized word embeddings. ACM/IMS Transactions on Data Science : TDS, 1, Article 6, 1–19.

Gerdon, F., Theil, C. K., Kern, C., Bach, R. L., Kreuter, F., Stuckenschmidt, H. and Eckert, K. (2020). Exploring impacts of artificial intelligence on urban societies with social simulations. 40. Kongress der Deutschen Gesellschaft für Soziologie, Online.

Review Activities

EPJ Data Science
EMNLP 2021 (computational social science track)
ACL-IJCNLP 2021 (computational social science track)

Teaching

AI in Industry (spring 2022, M.Sc.)
Team Project “Social Simulation” (spring 2021, M.Sc.)
dataakademie: “Natural Language Processing” (fall 2020, practitioners)
CS 704 Social Simulation Seminar (spring 2020, M.Sc.)
Team Project “Smart City” (spring 2019, M.Sc.)
IPSDS: SURV704 Computer-Based Content Analysis II (spring 2019 & 2020)
IPSDS: SURV703 Computer-Based Content Analysis I (fall 2018 & 2019)

Students

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