The paper “Using Semantic Linking to Understand Persons’ Networks extracted from Text” authored by Alessio P. Aprosio, Sara Tonelli, Stefano Menini, Giovanni Moretti has been accepted for publication on “Frontiers in Digital Humanities”.

Abstract: In this work, we describe a methodology to interpret large persons’ networks extracted from text by classifying cliques using theDBpedia ontology. The approach relies on a combination of NLP, Semantic web technologies and network analysis. The classificationmethodology that first starts from single nodes and then generalises to cliques is effective in terms of performance and is able todeal also with nodes that are not linked to Wikipedia. The gold standard manually developed for evaluation shows that groups ofco-occurring entities share in most of the cases a category that can be automatically assigned. This holds for both languagesconsidered in this study. The outcome of this work may be of interest to enhance the readability of large networks and to providean additional semantic layer on top of cliques. This would greatly help humanities scholars when dealing with large amounts oftextual data that need to be interpreted or categorised. Furthermore, it represents an unsupervised approach to automaticallyextend DBpedia starting from a corpus.