Methodological Directions for the Study of Memes

Introduction

This chapter seeks to anchor meme research to the actual production, by offering an updated typology of some of the most popular memetic formats spreading online. In so doing, it also proposes a methodological toolkit to analyse Internet memes, addressing the challenges posed by their multimodal and heterogeneous realizations. In a society where “what we see is often more important than what we hear or read” (Rose 2016, p. 2), multimodal user-generated content has carved out an increasingly relevant role in online interactions. In this scenario, Internet memes have gained foot as an engaging tool for users to express themselves in an ironic format, often combining visual and textual material (Milner, 2016; Shifman, 2014). To date, research on memes has been concerned with their contribution to the expression of political ideas and of subcultural identity (Ross and Rivers, 2019; Denisova, 2019; Gal et al., 2016). However, such analyses are mostly based on cherry-picked samples, which hardly account for the wide range of possible meme layouts and patterns circulating on the web. By limiting the investigation to well-known and recognized memetic frames (e.g. the so-called ‘Image Macros”), many scholars have circumvented the question of defining memes from an empirical point of view. In fact, despite the several and partly overlapping theoretical definitions (Knobel and Lankshear, 2007; Davison, 2012), there is little indication on how to empirically approach the study of memes. On a general level, existing research has barely started to explore the boundaries of this complex and multifaceted phenomenon. To address this issue, this chapter undertakes an empirical analysis which combines digital and qualitative methods, investigating which popular memes and recurring formats are circulating on Instagram within the Italian cultural context. With a user base mostly composed by people from 18 to 35 years old (Chen, 2020), Instagram has a strong influence on youth culture, identity, and perceptions of the world. Memes, which cover a considerable percentage of the visual formats of the platform (Hu et al., 2014), are considered not only a form of entertainment but also an identity building device (DeCook, 2018), as well a tool to comment on political and social issues (Fauzi et al., 2020).

The initial dataset, which has been gathered with digital methods (Rogers, 2013) following the general hashtag #memeitaliani, features 47.443 static image memes. A sample of 1000 items has been selected by engagement and manually tagged according to relevant features, derived both from existing literature (Shifman, 2013) and the data itself. By adopting this data driven approach, it is possible to identify memes from non-memetic material on the basis of a shared characteristic, i.e. the degree of manipulation. Findings show that manual coding provides the researcher with a systemization of meme production into four standardised formats, showing recurrent patterns of sense-making and irony construction: Mono, Reaction, Panel, and Box. The last section further explores Reaction memes by using Discourse Analysis (Fairclough, 1995). It is argued that Reaction memes trigger the identification with the users, by both representing commonly shared life situations and employing textual linguistic cues, such as the ‘Script’ or of the ‘When’ pattern.