A Corpus-Based Analysis of Digital Communication Patterns in Mobile Messaging Platforms

Abstract

Mobile phones have transformed everyday communication, with platforms such as WhatsApp and Telegram becoming routine spaces for interaction. This study examines linguistic practices in these environments through a small, carefully curated corpus of anonymized mobile messages collected by university students. The analysis focuses on lexical choice, syntactic structure, language switching, and deployment of emojis, abbreviations, and other additional multimodal elements. Using corpus-linguistic methodologies, specifically AntConc and SketchEngine, the study identifies collocation tendencies, recurring patterns, frequent word pairings, and discourse practices that shape meaning in mobile messaging. The findings show that mobile communication represents a distinct mode of interaction that diverges from traditional speech and writing to reflect fast, informal, and socially embedded conversation. They also reveal how young adults adapt language creatively to meet the demands of digital exchange. The study further considers how mobile message corpora can support language teaching by providing learners with authentic instances of contemporary communication use.