Digital Visual Communication in Social Media Platforms
Summary
Digital visual communication encompasses the creation, sharing and interpretation of images, graphics and video content within social media environments. This field examines how users deploy visual artefacts—from selfies and infographics to short-form videos and memes—to establish identity, foster community and influence public discourse. Platforms such as Instagram, TikTok, Twitter and Snapchat each offer distinct visual affordances and editing tools that shape aesthetic conventions, user behaviour and the dissemination of information. Researchers explore the interplay of algorithmic curation, platform vernaculars and user motivations, analysing how automated recommendation systems and user interface designs guide attention to specific visual genres and narratives. Advances in computer vision and machine learning enable large-scale analyses of pose recognition, image sentiment and meme evolution, while qualitative methods illuminate the cultural practices and ethical dimensions of visual sharing. The global significance of this work extends across marketing, political communication, social activism and mental health, offering insights into both the empowering potential and the societal challenges of living in an increasingly image-driven digital world.
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Digital Visual Communication in Social Media Platforms publication trend
The graph below shows the total number of articles in digital visual communication in social media platforms across all publications each year (not limited to Nature Index journals).
Technical terms
Visual affordances: Platform-specific features and tools that enable or constrain the creation and sharing of visual content, such as filters or story formats.
Multimodal communication: The integration and co-occurrence of multiple semiotic modes—visual, textual and auditory—within a single piece of content.
Algorithmic curation: Automated processes used by platforms to select and prioritise content in users’ feeds based on user behaviour, engagement metrics or inferred preferences.
Cross-platform analysis: Comparative research methods designed to examine visual content and user interactions across two or more social media platforms.
Pose detection: Computational technique for identifying and analysing human body positions in images or video, often used to quantify patterns of self-presentation.
References
- Unveiling digital mirrors: Decoding gendered body poses in instagram imagery. Computers in Human Behavior (2025).
- Visual cross-platform analysis: digital methods to research social media images. Information Communication & Society (2018).
- Snap-along ethnography: Studying visual politicization in the social media age. Ethnography (2022).
- Discourses of social media amongst youth: An ethnographic perspective. Discourse Context & Media (2022).
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