CHALLENGES IN REPRESENTING MULTIMODAL DISCOURSE IN CORPUS LINGUISTICS: A CASE STUDY OF SOCIAL MEDIA COMMUNICATION

Аннотация

Social media platforms have transformed human communication by integrating multiple semiotic modes—text, images, emojis, video, and audio—into a single discourse space. This multimodal nature poses substantial challenges for corpus linguistics, a field traditionally focused on textual data. This paper investigates the key methodological, technical, and theoretical challenges of representing multimodal discourse in social media corpora. Through a case study approach, it critically examines existing annotation frameworks, data management strategies, and multimodal integration techniques. Finally, the paper proposes directions for developing richer, more comprehensive multimodal corpora that reflect the complexity of contemporary digital communication. Keywords: multimodal discourse, corpus linguistics, social media, annotation, data integration, discourse analysis, digital communication.