Timing: 01.10.2020 – 31.12.2024
Funding: Förderung des Bundesministeriums für Bildung und Forschung von KI-Nachwuchswissenschaftlerinnen

About the Project: The DynSoDA project will model the discourse aspects of language together with the deep representations of user characteristics and latent social network profiles derived from online dialogues. In contrast to current approaches, user representations will be treated as dynamically contextual. The project further envisions the use of transfer learning techniques at multiple levels of abstraction to work robustly across a range of NLP tasks related to social discourse (such as opinion detection, hate speech identification, or argument persuasiveness prediction).

Principal Investigators:  Prof. Dr. Lucie Flek

Publications: 
- Perspective Taking through Generating Responses to Conflict Situations, J Plepi, C Welch, L Flek, Findings of the Association for Computational Linguistics ACL 2024, 6482-6497
- Do Multilingual Large Language Models Mitigate Stereotype Bias? S Nie, M Fromm, C Welch, R Görge, A Karimi, J Plepi, NA Mowmita, ..., arXiv preprint arXiv:2407.05740
- EmPO: Emotion Grounding for Empathetic Response Generation through Preference Optimization, O Sotolar, V Formanek, A Debnath, A Lahnala, C Welch, L FLek, arXiv preprint arXiv:2406.19071
- A Perspectivist Corpus of Numbers in Social Judgements, M May, L Flek, C Welch, Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP …
- Archetypes and Entropy: Theory-Driven Extraction of Evidence for Suicide Risk, V Varadarajan, A Lahnala, AV Ganesan, G Dey, S Mangalik, AM Bucur, ..., Proceedings of the 9th Workshop on Computational Linguistics and Clinical …
- Corpus Considerations for Annotator Modeling and Scaling, OO Sarumi, B Neuendorf, J Plepi, L Flek, J Schlötterer, C Welch, arXiv preprint arXiv:2404.02340