Overview
This paper makes a case for integrating frameworks from two different knowledge domains, rhetorical studies and ecological studies, to catalog, monitor, and study digital image meme data, in order to support a more robust understanding of how memes produce and disseminate online narratives. In the digital public sphere, the primacy of image-based communication motivates an over-reliance on the image meme for public argumentation. Despite its ubiquity, the image meme format is currently understudied in large scale digital data analyses, relative to text -based formats such as natural language and hashtags. We argue that using a rhetorical approach (which emphasizes message form and audience) in large-scale analyses of multimedia and other digital artifacts can enhance analytic tools for categorizing, indexing, searching, and modeling online discourse. Further, by integrating a rhetorical and an ecosystem approach to studying digital discourse, we can formally trace multimedia rhetorical artifacts like image memes across platforms, media types, and languages. Combined rhetorical and ecosystem analyses can reveal how digital artifacts like image memes create, sustain, and disrupt public narratives and, thereby, socio-political dynamics. Three key elements of our approach are a) recognizing how parsimony and polysemy give image memes narrative power, b) focusing on how image memes engage audiences through identity construction, and c) applying “Rhetorical Ecosystem” mapping, based upon toolkit transfer and system design implications. Drawing from concepts in rhetoric, ecology, and complex systems analysis we introduce a Digital Rhetorical Ecosystem three-tiered model (DRE3) to explain how memes impact public narratives and beliefs. We then explore implications of this DRE3 model for the design and development of systems for computational analysis of digital discourse.
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Methods and contributions
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Findings and contributions
- The authors argue that a rhetorical approach, emphasizing message form and audience, can improve large-scale tools for categorizing, indexing, searching, and modeling online discourse.
- They introduce the Digital Rhetorical Ecosystem three-tiered model (DRE3) to explain how memes affect public narratives and beliefs.
- They suggest current software can perform many sub-tasks of image-meme rhetorical analysis, with crowd-sourced annotation filling gaps where software is insufficient.
- Despite meme polysemy, the authors hold that it is possible and useful to identify the dominant argument encoded in an image meme.
- The paper closes with recommendations, such as curating patterns in image-meme rhetorical structure and protecting user identity, privacy, and preferences in cataloging schemes.
Methods
- Mapping concepts between rhetorical studies and ecology — The authors extend existing links between rhetoric and ecology, proposing ecological-rhetorical mappings (e.g., predator-prey style relations between communities) for digital discourse.
- Three-phase DRE3 analysis: entity, rhetorical, hidden-state identification — Image memes are analysed in three phases: identifying visual entities, tracing their relationships into claims and warrants, and inferring deeper hidden states of the ecosystem.
- Qualitative 'boutique' case analyses of two image memes — The DRE3 model is applied to one meme without text (Bob Ross / G.W. Bush) and one with text (Bill Murray) to show the three tiers.
- Blueprint of a meme-analysis pipeline styled as a SCADA system — The authors sketch a Supervisory, Control, and Data Acquisition style pipeline for collecting, annotating, analysing, and disseminating image memes at scale.
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