<![CDATA[This article is a literature review that connects three hot topics in politeness research: cross-cultural pragmatics, online discourse, and computational approaches. The core article draws on Nurjaleka et al. (2021), who discussed how Japanese and Javanese speakers perceive politeness differently. They found that Japanese speakers emphasize honorifics and Javanese speakers emphasize indirectness. However, this study was based on survey data rather than discourse analysis. Kavanagh (2016), on the other hand, demonstrated how bloggers in American and Japanese communities use emoticons to convey kindness and establish supportive identities in online interactions. However, the findings were limited to a small sample and specific to one platform. In contrast, a computer study by Danescu-Niculescu-Mizil et al. (2013) actually broadened the field of politeness research by automatically identifying signals in millions of communications, including modal verbs, greetings, and expressions of thanks. Recent studies have shown how machine learning can enhance politeness classification while also revealing cultural subtleties (e.g., Priya, Firdaus, & Ekbal, 2024; Aljanaideh et al., 2025). When paired with existing studies, it shows distinct gaps and complementary strengths. In short, online research emphasizes multimodal identity construction, computational work enables scalability, and cross-cultural studies provide a cultural foundation. Future research is expected to fully encompass all these perspectives. Keywords: literature review, politeness, identity, online discourse, cross-cultural pragmatics, computational linguistics]]>
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