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Fields such as the philosophy of language, continental philosophy, andliterary studies have long established that human language is, at its essence,ambiguous and that this quality, although challenging to communication,enriches language and points to the complexity of human thought. On the otherhand, in the NLP field there have been ongoing efforts aimed at disambiguationfor various downstream tasks. This work brings together computational textanalysis and literary analysis to demonstrate the extent to which ambiguity incertain texts plays a key role in shaping meaning and thus requires analysisrather than elimination. We revisit the discussion, well known in thehumanities, about the role ambiguity plays in Henry James' 19th centurynovella, The Turn of the Screw. We model each of the novella's two competinginterpretations as a topic and computationally demonstrate that the dualitybetween them exists consistently throughout the work and shapes, rather thanobscures, its meaning. We also demonstrate that cosine similarity and wordmover's distance are sensitive enough to detect ambiguity in its most subtleliterary form, despite doubts to the contrary raised by literary scholars. Ouranalysis is built on topic word lists and word embeddings from various sources.We first claim, and then empirically show, the interdependence betweencomputational analysis and close reading performed by a human expert.

Sensing Ambiguity in Henry James' "The Turn of the Screw"