Deconstructing WhatsApp Emojis and Emotions through Semiotic Principles' Prisms
Year: 2025
Type: article
Abstract: Emojis have become an integral part of everyday digital communication, yet their deeper semiotic and emotional complexities remain underexplored. This study investigates how WhatsApp emojis function as semiotic signs, conveying and shaping emotional meaning in digital interactions. Drawing on Saussurean structural semiotics and Peircean triadic semiotics, the research examines how users encode, interpret, and negotiate emotions through emojis, considering cultural, generational, and relational contexts. A qualitative exploratory design was employed, combining digital ethnography and semiotic analysis of anonymised WhatsApp chat histories from twenty purposively selected participants aged 18–35, supplemented by semi-structured interviews. This study analysed 20 chat histories, and focused on the denotative and connotative meanings of emojis and their interaction with textual messages to convey humour, affection, frustration, and relational nuance. Findings reveal that emojis operate as multimodal communicative tools whose meanings are context-dependent, culturally mediated, and relationally nuanced. They enhance emotional expression, complement or substitute verbal text, and function as complex signs characterised by arbitrariness, iconicity, indexicality, and social convention. The study contributes to the literature by providing a comprehensive semiotic understanding of WhatsApp emoji use among Nigerian users, grounded in authentic chat interactions, highlighting the role of visual-emotional literacy in contemporary digital communication. Practical implications include the need for emoji literacy in communication training, culturally sensitive platform design, and user awareness of context to avoid miscommunication.
Authors: Greatandy Victor Iguoba, Obinna Johnkennedy Chukwu, Ph.D, BL
Institutions: Edo State University Uzairue, Ambrose Alli University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7092198150
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