A Pragmatic Analysis of the Deictic Aspect in the Novel Wonder by R.J. Palacio 2012
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Deixis, Wonder, Pragmatics, Linguistic analysis, Person deixisAbstrak
This study aimed to analyze the pragmatic function and distribution of deixis in the novel Wonder by R.J. Palacio, specifically focusing on how deictic expressions contribute to conveying character viewpoints and structuring the narrative. A qualitative descriptive method under the lens of pragmatics was applied, using content analysis to examine deictic expressions extracted from the novel's text. The results confirmed that the novel utilizes all five categories of deixis (person, temporal, spatial, discourse, and social). Person deixis emerged as the most frequent category, a dominance directly linked to the novel's multiple first-person narrative structure which relies heavily on pronouns like I, me, and my to anchor each perspective. Each deictic type fulfills a unique structural role: person deixis conveys emotional perspective, while temporal, spatial, discourse, and social deixis organize events, setting, narrative connections, and relational dynamics, respectively. The findings underscore that deixis functions as a powerful narrative strategy rather than merely a linguistic feature, effectively drawing the audience into the characters’ experiences and profoundly shaping reader reception and emotional connection. This demonstrates the critical role of linguistic features in literary characterization and narrative flow. A primary limitation of the study is its restriction to a single novel, which excludes the analysis of paralinguistic features that often accompany deixis in real-life communication. Based on these findings, it is recommended that future researchers explore deixis in other literary genres or combine its analysis with other pragmatic concepts like speech acts and implicature, while educators should integrate deictic analysis to enhance students' interpretive skills, and computational linguistics researchers may use these insights to improve context-sensitive language models.
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