Acknowledgement Text

Research on acknowledgement text focuses on automatically extracting and classifying information within acknowledgements of scientific publications, aiming to uncover insights into funding sources, collaborations, and research trends. Current approaches leverage natural language processing (NLP) techniques, particularly named entity recognition (NER) models like those based on BERT and Flair embeddings, to identify entities such as funding agencies, individuals, and institutions. This automated analysis overcomes limitations of previous manual methods, enabling large-scale studies of acknowledgement patterns across diverse scientific domains and potentially revealing hidden aspects of the scientific reward system and research ecosystem.