Abstract

Fiction has come to play an essential part in human culture and life in recent centuries. Because of its importance, the language or discourse of fiction has been widely studied. Discerning the evolutionary pattern of language in fiction is greatly helpful in understanding the changes in human culture and society. However, most previous studies on literary language that made use of quantitative or computational methods restricted themselves to a few authors or groups and only took into account a relative short span of time. Furthermore, most of the quantitative analysis therein was based on a primary and rather primitive algorithm that summarizes the frequencies of linguistic units in corpora. To overcome these limitations, this study uses semantic similarity as computed by semi-supervised methods to examine diachronic changes. In this study, the three large-scale corpora representing the English language and English fiction were used to investigate the evolutionary patterns concerning diachronic concreteness/imageability. The data from the two measures are well mapped and shown to support the argument that English fiction, as a special genre, exhibits an evolutionary tendency toward increasing concreteness/imageability. This indicates that modern fiction may have become increasingly important in human society, but easier to read and process in words than 19th century English fiction. This study proposed that learnability, genre difference, the changes of population size, and the other factors might have caused the systemic change. The current study is thus an important contribution to understanding the evolutionary trend of language in fiction as well as understanding the development of the English language as a whole. This study creates a novel quantitative methodology and applies this to the examination of diachronic changes of language in literary works.

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