Citation Count

Citation count, a widely used metric for assessing scientific impact, is the subject of ongoing research aimed at improving its accuracy and predictive power. Current efforts focus on developing machine learning models, including neural networks like multilayer perceptrons and BERT-based approaches, to predict citation counts by leveraging textual information from research papers, citation networks, and even incorporating qualitative aspects like sentiment and intent. These advancements aim to provide more nuanced and reliable assessments of research influence, potentially leading to better resource allocation, improved research evaluation, and a more accurate understanding of knowledge dissemination within scientific fields.