Abstract
Any text, be it written by humans or generated by computers, must choose a specific style and be consistent. Textual style is based on the genre to which the text should belong. Each genre has its unique characteristics based on the style of narration, the topic, the target audience, and the author’s intentions. Thus, in order to write or produce better passages, a finer-grained style checker sensitive to differences among genres is to be developed. We propose a foundational method for this purpose: the flexible accumulation of data of the style features of atomic expressions based on any kind of contrastive sets of texts representing the good and bad examples for the targeted genre, an analysis of a given text using the style features, and a visualization to effectively help the author detect anomalies for the targeted genre. Any type of genre-sensitive style checker will implement our method or similar ones.
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