Comparing Writing Styles using Word Embedding and Dynamic Time Warping
This addresses a domain-specific problem for literary analysis, but it appears incremental as it applies existing methods (word embeddings and dynamic time warping) to a new dataset of novels.
The study tackled the problem of comparing writing styles in classic novels by quantifying sentiment flow as signals in word embedding space and using dynamic time warping for comparison, but no concrete results or numbers were reported.
The development of plot or story in novels is reflected in the content and the words used. The flow of sentiments, which is one aspect of writing style, can be quantified by analyzing the flow of words. This study explores literary works as signals in word embedding space and tries to compare writing styles of popular classic novels using dynamic time warping.