“Don’t worry, it’s just noise’”: quantifying the impact of files treated as single textual units when they are really collections

NLP4DH (ICON) 2021  ·  Thibault Clérice ·

Literature works may present many autonomous or semi-autonomous units, such as poems for the first or chapter for the second. We make the hypothesis that such cuts in the text’s flow, if not taken care of in the way we process text, have an impact on the application of the distributional hypothesis. We test this hypothesis with a large 20M tokens corpus of Latin works, by using text files as a single unit or multiple “autonomous” units for the analysis of selected words. For groups of rare words and words specific to heavily segmented works, the results show that their semantic space is mostly different between both versions of the corpus. For the 1000 most frequent words of the corpus, variations are important as soon as the window for defining neighborhood is larger or equal to 10 words.

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