Symbolic signals on Instagram: how visual media shapes engagement, emotion, trust, and diffusion
Abstract Throughout history, visual symbols have served as powerful tools for communication, uniting communities, shaping narratives, and driving social movements. From traditional media such as pamphlets and murals to contemporary public art, these symbols carry profound social, cultural, and political (SCP) significance, fostering identity, unity, and shared values through the framework of symbolic interaction theory. In the digital era, platforms like Instagram have revolutionized the creation, dissemination, and interpretation of visual symbols, enabling rapid sharing and offering early indicators of campaign effectiveness. This study examines the role of symbolic imagery in shaping user engagement, creating emotional responses, establishing trust, and affecting diffusion dynamics, focusing on Taiwan’s recent election-related disinformation debunking campaign. Analyzing 3,097 Instagram posts collected between January 13 and January 27, 2024, we employed advanced computational models, including GPT-4o and Gemini Pro Vision, to identify SCP symbols embedded in the content. Our findings reveal that posts featuring symbolic imagery significantly outperform those without such elements in generating user interactions, evoking emotional resonance, enhancing perceived trust, and achieving faster diffusion. In particular, posts that incorporate cultural symbols demonstrated the highest impact, strongest resonance, and fastest diffusion among the audience. These insights offer valuable, data-driven strategies for policymakers and content creators engaged in strategic communication to leverage visual symbols effectively in combating misinformation and fostering meaningful public discourse in today’s hyper-connected digital landscape.
Authors
- Diwash Poudel
- Nitin Agarwal (ORCID: https://orcid.org/0000-0002-5612-4753)
- Mayor Inna Gurung (ORCID: https://orcid.org/0009-0003-5828-3189)
- Md. Monoarul Islam Bhuiyan
Institutions
- University of Arkansas at Little Rock (US)
- International Computer Science Institute (US)
Publication Details
- Journal
- Social Network Analysis and Mining
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1007/s13278-025-01469-0
- Citations
- 2
- Primary Topic
- Misinformation and Its Impacts
- Type
- article
- Field-Weighted Citation Impact
- 8.40
Funders
- National Science Foundation
- U.S. Department of Defense
- Arkansas Research Alliance
- Defense Advanced Research Projects Agency
- U.S. Air Force
- Advanced Research Projects Agency
- Office of the Under Secretary of Defense
- Office of Naval Research
- Army Research Office
- Air Force Research Laboratory