Utilizing citation network structure to predict paper citation counts: A Deep learning approachQihang Zhao, Xiaodong Feng2021-12-09articleJournal of Informetrics49 citationsclosedNo readable copy stored yet — this record is metadata only.scientometrics and bibliometrics researchComplex Network Analysis TechniquesWeb visibility and informetricsAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 49 citations exist upstream.References2013Quantifying Long-Term Scientific Impact2004Sleeping Beauties in science2015Defining and identifying Sleeping Beauties in science2013Which factors help authors produce the highest impact research? Collaboration, journal and document properties2015The advantage of short paper titles2014Citation impact prediction for scientific papers using stepwise regression analysis2020Predicting the citation counts of individual papers via a BP neural network2019Predicting the citations of scholarly paperCited by2024Unleashing the power of AI: a systematic review of cutting-edge techniques in AI-enhanced scientometrics, webometrics and bibliometrics2023Predicting article quality scores with machine learning: The U.K. Research Excellence Framework2023Citation counts prediction of statistical publications based on multi-layer academic networks via neural network model2023Deep learning for predicting patent application outcome: The fusion of text and network embeddings2022Patent landscape and key technology interaction roadmap using graph convolutional network – Case of mobile communication technologies beyond 5G