English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Natural Language Processing and Machine Learning have considerably advancedComputational Literary Studies. Similarly, the construction of co-occurrencenetworks of literary characters, and their analysis using methods from socialnetwork analysis and network science, have provided insights into the micro-and macro-level structure of literary texts. Combining these perspectives, inthis 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 andvisualise the narrative style that characterises Tolkien's works. Addressingcharacter classification, embedding and co-occurrence prediction, we furtherinvestigate the advantages of state-of-the-art Graph Neural Networks over apopular word embedding method. Our results highlight the large potential ofgraph learning in Computational Literary Studies.

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