Abstract

This paper explores the semiotic landscape of online discourse within contemporary social media, employing a corpus-based methodology to analyze both linguistic and visual modalities. By examining a large dataset of social media posts, we investigate how meaning is constructed and conveyed through the interplay of text, images, and other visual elements. Our analysis focuses on identifying prevalent semiotic codes and patterns, exploring their relationship to user engagement and sentiment, and ultimately, understanding how these multimodal communicative strategies shape online social interaction. The findings contribute to a deeper understanding of the complexities of digital communication and the evolving role of semiotics in the online environment. We address the limitations of previous research by incorporating a novel, computationally-assisted approach to visual semiotic analysis and by focusing on the emergent properties of multimodal meaning-making.