One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium

• URL: http://arxiv.org/abs/2210.07871v1
• Date: Fri, 14 Oct 2022 14:47:56 GMT
• Title: One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium
• Authors: Vincenzo Perri, Lisi Qarkaxhija, Albin Zehe, Andreas Hotho, Ingo Scholtes
• Abstract summary: 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.
• Score: 3.0448872422956432
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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