%0 Generic %1 perri2022graph %A Perri, Vincenzo %A Qarkaxhija, Lisi %A Zehe, Albin %A Hotho, Andreas %A Scholtes, Ingo %D 2022 %K caidas-area-comp-lit-stud %T One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium %U http://arxiv.org/abs/2210.07871 %X 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.

@misc{perri2022graph, 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.}, added-at = {2023-02-20T18:03:26.000+0100}, author = {Perri, Vincenzo and Qarkaxhija, Lisi and Zehe, Albin and Hotho, Andreas and Scholtes, Ingo}, biburl = {https://www.bibsonomy.org/bibtex/2070ca503bc1201d2d04955b729b27dee/ifland}, interhash = {d9ca320ad5969855cec637114e0324e3}, intrahash = {070ca503bc1201d2d04955b729b27dee}, keywords = {caidas-area-comp-lit-stud}, note = {cite arxiv:2210.07871}, timestamp = {2023-02-20T18:03:26.000+0100}, title = {One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium}, url = {http://arxiv.org/abs/2210.07871}, year = 2022 }