Racial color blindness: a corpus-assisted discourse analysis of social media reactions to Disney's Little Mermaid teaser - Ahmad Suhaili; Frans Sayogie; Muhammad Farkhan; Farizka Ummi Arif (Penerbit Universiti Kebangsaan Malaysia, 2025)
Social media, as an interactive platform, reflects society's reality. This study explored how racial color blindness ideology is reinforced and reshaped through users' discourse patterns on social media platforms. It refers to the ongoing process through which individuals collectively redefine, negotiate, and perpetuate color-blind ideologies through their digital interactions and responses to racially charged media content. This research specifically aimed to identify linguistic patterns and discourse strategies that demonstrate how social media users' responses to Disney's The Little Mermaid teaser contribute to the maintenance and transformation of racial color blindness ideology in contemporary digital spaces. Racial color blindness persists as a critical issue in contemporary media representation, with this study investigating how social media users construct and negotiate racial discourse through their responses to Disney's casting decisions in The Little Mermaid teaser. Utilizing a Corpus-Assisted Discourse Studies (CADS) approach, the research analyzed 75,000 YouTube comments (948,610 tokens) for quantitative corpus analysis and supplementary Twitter (hereinafter referred to as X) data for qualitative discourse interpretation using Stuart Hall's encoding-decoding theory. Data collection involved multi-platform scraping through the YouTube API and X data collection, with corpus processing through AntConc software, integrating quantitative corpus linguistic techniques with qualitative discourse analysis. The multi-platform analysis revealed three primary response categories: dominant (embracing diversity), negotiated (ambivalent representation), and oppositional (rejecting racial recasting).