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Automated research analyses are becoming more and more important as the volume of research items grows at an increasing pace. We pursue a new direction for the analysis of research dynamics with graph neural networks. So far, graph neural networks have only been applied to small-scale datasets and primarily supervised tasks such as node classification. We propose to use an unsupervised training objective for concept representation learning that is tailored towards bibliographic data withdoi:10.18420/inf2019_26 dblp:conf/gi/GalkeMSTFST19 fatcat:zzjikey6obc4hkh7fpc2hzp2hy