Speaker: Vincenzo Perri, Lisi Qarkaxhija, Albin Zehe, Andreas Hotho and Ingo Scholtes
Affiliation: (1) Data Analytics Group, Department of Informatics(IfI), Universität Zürich, CH-8050 Zürich, Switzerland; (2) Chair of Informatics XV - Machine Learning for Complex Networks, Center for Artificial Intelligence and Data Science (CAIDAS), Julius-Maximilians-Universität Würzburg, D-97074 Würzburg, Germany; (3) Chair of Informatics X - Data Science, Center for Artificial Intelligence and Data Science (CAIDAS), Julius-Maximilians-Universität Würzburg, D-97074 Würzburg, Germany
Title: One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien’s Legendarium
Abstract: Natural Language Processing and Machine Learning have considerably advanced Computational Literary Studies. Similarly, the construction of co-occurrence networks of literary characters, and their analysis using methods from social network analysis and network science, have provided insights into the micro- and macro-level structure of literary texts. Combining these perspectives, in this work we study character networks extracted from a text corpus of J.R.R. Tolkien’s Legendarium. We show that this perspective helps us to analyse and visualise the narrative style that characterises Tolkien’s works. Addressing character classification, embedding and co-occurrence prediction, we further investigate the advantages of state-of-the-art Graph Neural Networks over a popular word embedding method. Our results highlight the large potential of graph learning in Computational Literary Studies.