Word Embedding Models and the Hybridity of Newspaper Genres.

The authors discuss the fluid nature of genre, emphasizing its contextual dependence and historical evolution. They argue that genre defies fixed definitions and can change over time and across readership. Through computational text analysis, particularly employing word embedding models, researchers can navigate the intricate landscape of nineteenth-century newspapers, uncovering hidden relationships between genres and challenging conventional taxonomies. This approach highlights the complexity of genre and offers insights into historical writing and reader perceptions.