文章基本信息

标题：Multiple Communication Channels in Literary Texts
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作者：Emilio Matricciani
期刊名称：Open Journal of Statistics
印刷版ISSN：2161-718X
电子版ISSN：2161-7198
出版年度：2022
卷号：12
期号：4
页码：486-520
DOI：10.4236/ojs.2022.124030
语种：English
出版社：Scientific Research Publishing
摘要：The statistical theory of language translation is used to compare how a literary character speaks to different audiences by diversifying two important linguistic communication channels: the “sentences channel” and the “interpunctions channel”. The theory can “measure” how the author shapes a character speaking to different audiences, by modulating deep-language parameters. To show its power, we have applied the theory to the literary corpus of Maria Valtorta, an Italian mystic of the XX-century. The likeness index , ranging from 0 to 1, allows to “measure” how two linguistic channels are similar, therefore implying that a character speaks to different audiences in the same way. A 6-dB difference between the signal-to-noise ratios of two channels already gives IL ≈ 0.5, a threshold below which the two channels depend very little on each other, therefore implying that the character addresses different audiences differently. In conclusion, multiple linguistic channels can describe the “fine tuning” that a literary author uses to diversify characters or distinguish the behavior of the same character in different situations. The theory can be applied to literary corpora written in any alphabetical language.
关键词：Alphabetical LanguageCommunication ChannelsInformationLikeness In-dexLiterary CharacterLiterary TextMaria ValtortaSignal-to-Noise RatioSymmetry Index