The chapter proposes an empirically oriented analysis of the memetic production on Instagram. Defined as multimodal cultural artifacts, combining visual and textual material to convey humoristic messages, internet memes proliferate across the web, spawning new popular formats and layouts. However, many scholars still rely on outdated conceptualisations or limited samples for their studies. To anchor investi- gation on memes to the actual production, the research answers the questions: (1) Which meme formats are currently circulating online? (2) How do popular meme formats convey their message? To this end, a dataset of static images collected on Instagram was examined with qualitative visual and discourse analysis. Findings point at the possibility to adopt a bottom-up approach to recognize and classify memes, exploiting shared features of content and form. Furthermore, this categorization offers insights on the most productive mechanisms of meme production: contextually, results show a tendency towards formats that trigger identification, leveraging on relatable life situations.
Methodological Directions for the Study of Memes / G. Giorgi (ADVANCES IN KNOWLEDGE ACQUISITION, TRANSFER AND MANAGEMENT BOOK SERIES). - In: Handbook of Research on Advanced Research Methodologies for a Digital Society Advances in Knowledge Acquisition, Transfer, and Management / [a cura di] G. Punziano, A. Delli Paoli. - Hershey : IGI Global, 2021. - ISBN 9781799884736. - pp. 627-663 [10.4018/978-1-7998-8473-6.ch036]
Methodological Directions for the Study of Memes
G. Giorgi
2021
Abstract
The chapter proposes an empirically oriented analysis of the memetic production on Instagram. Defined as multimodal cultural artifacts, combining visual and textual material to convey humoristic messages, internet memes proliferate across the web, spawning new popular formats and layouts. However, many scholars still rely on outdated conceptualisations or limited samples for their studies. To anchor investi- gation on memes to the actual production, the research answers the questions: (1) Which meme formats are currently circulating online? (2) How do popular meme formats convey their message? To this end, a dataset of static images collected on Instagram was examined with qualitative visual and discourse analysis. Findings point at the possibility to adopt a bottom-up approach to recognize and classify memes, exploiting shared features of content and form. Furthermore, this categorization offers insights on the most productive mechanisms of meme production: contextually, results show a tendency towards formats that trigger identification, leveraging on relatable life situations.File | Dimensione | Formato | |
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