TY  - CPAPER
U1  - Konferenzveröffentlichung
A1  - Becker, Maria
A1  - Han, Kanyao
A1  - Werthmann, Antonina
A1  - Rezapour, Rezvaneh
A1  - Lee, Haejin
A1  - Diesner, Jana
A1  - Witt, Andreas
ED  - Calzolari, Nicoletta
ED  - Kan, Min-Yen
ED  - Hoste, Veronique
ED  - Lenci, Alessandro
ED  - Sakti, Sakriani
ED  - Xue, Nianwen
T1  - Detecting impact relevant sections in scientific research
T2  - The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
N2  - Impact assessment is an evolving area of research that aims at measuring and predicting the potential effects of projects or programs on a variety of stakeholders. While measuring the impact of scientific research is a vibrant subdomain of impact assessment, a recurring obstacle in this specific area is the lack of an efficient framework that facilitates labeling and analysis of lengthy reports. To address this issue, we propose, implement, and evaluate a framework for automatically assessing the impact of scientific research projects by identifying pertinent sections in research reports that indicate potential impact. We leverage a mixed-method approach that combines manual annotation with supervised machine learning to extract these passages from project reports. We experiment with different machine learning algorithms, including traditional statistical models as well as pre-trained transformer language models. Our results show that our proposed method achieves accuracy scores up to 0.81, and that our method is generalizable to scientific research from different domains and different languages.
KW  - impact detection
KW  - project reports
KW  - annotation
KW  - mixed-methods
KW  - machine-learning
KW  - Forschung
KW  - Annotation
KW  - Wirkungsanalyse
KW  - Sprachdaten
KW  - Infrastruktur
Y1  - 2024
U6  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-127100
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-127100
UR  - https://aclanthology.org/2024.lrec-main.424/
SP  - 4744
EP  - 4749
PB  - European Language Resources Association (ELRA)
CY  - Paris
ER  -