The research is aimed at understanding information contained in PIMs and how users learn from them. One of the main problems in Internet Meme (IM) research is the lack of systematic tools and frameworks that researchers can use to analyse IMs. To address this gap in the literature, this PhD proposes to create a tool (Meta-Meme) for analysis that combines statistical techniques with machine learning. Meta-Meme helps researchers establish a conventional way to start the analysis based on aggregate IM data.
The project offers a systematic account of PIMs as a political psychology phenomenon and experimentally measures informational power. By understanding how PIMs transmit information, this research raises awareness of the hidden influence of PIMs on digital democracy.
The literature on tools for the analysis of memes is increasing (for an overview see Beskow et al., 2020) suggesting that a fully automated analysis of IMs can be performed. Different machine learning techniques have been employed, on different types of memes and media formats (Vlad et al., 2020). There is yet to emerge a tool for the analysis of internet memes that reflects the needs of different researchers. This PhD focuses on PIMs as it has been suggested in the literature (Moody-Ramirez & Church, 2019) that this specific type of IM impacts online political discourse and digital politics. For example, according to Heiskanen (2017) PIMs have the ability to engage voters who wouldn’t normally participate in the electoral process.
Defining PIMs itself has been difficult, there is no commonly agreed scholarly definition. This PhD conceptualises PIMs as simply IMs that are political in nature or contain a political message. It is also important to assess how individual differences (ID) might influence user-level PIM engagement and information processing. Survey research has been employed in a few papers to analyse PIMs and users (Klein, 2019; Huntington, 2020). This PhD follows this strand of research and aims at addressing the informational potential of PIMs (McLoughlin & Southern, 2020).
The research requires two stages. Stage A creates a tool (Meta-Meme) for researchers to perform systematic IMs analysis based on Content-Context-Structure of IMs. To demonstrate and validate the tool the PhD will reproduce published analyses of PIMs during political events. Meta-Meme needs to be able to recognise memes, then analyse and produce a summary output at the request of researchers. This will allow us to understand the information present in PIMs. The tool will also serve as a database and clustering of PIMs for stage B.
Stage B uses survey research to assess the extent to which PIMs can transfer their information to users. Using correlational and experimental panel studies will allow us to establish whether and how PIMs can inform users through their content. Firstly, it establishes which political psychology frameworks and factors might relate to PIM engagement. Secondly, it assesses with a panel study whether users learn information from PIMs, which types and quantity of PIMs are more effective at informing users.