The Chinese translation and reception of The Alchemist: A python-based sentiment analysis and topic modeling of Douban reader reviews
DOI:
https://doi.org/10.5007/2175-7968.2026.e110841Keywords:
reader reception, sentiment analysis, topic modeling, The Alchemist, Douban reviewsAbstract
This study investigates the reception of Ding Wenlin’s translation of The Alchemist within the Chinese digital reading sphere, employing a computational approach that integrates SnowNLP sentiment analysis and LDA topic modeling on a corpus of Douban reviews. It examines three interrelated dimensions: emotional tendencies, thematic structures, and evaluative behaviors. Findings indicate a predominantly positive reception, with textual sentiment surpassing star ratings, reflecting readers’ nuanced affective engagement. Thematic analysis identifies five latent clusters—spiritual inspiration, reading experience, literary critique, gender and character reflection, and religious/philosophical metaphors—revealing a dialectical engagement in which readers internalize the “Personal Legend” motif while exercising critical scrutiny, particularly regarding stylistic choices and gender representation. Community evaluation patterns highlight a preference for substantive critique: low-rating reviews, though rare, attract disproportionate attention, signaling a collective prioritization of analytical depth over mere affective endorsement. Theoretically, the study enriches the empirical reception history of Brazilian literature in China and demonstrates the utility of digital humanities methods in cross-cultural translation studies. Practically, it offers insights for publishers and translators seeking to facilitate the reception of global literary works among Chinese readers.
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