A Multimodal Pragmatic Analysis of 2024 American Presidential elections

By examining selected cartoons, the study attempts to investigate the impact of the multimodal pragmatic approach on the analysis of candidate prospects in the 24 American Presidential elections. In addition, such cartoons and clusters within cartoons are intended to be employed as an inference tool to predict presidential candidates' highest probability of winning and highest percentage of losing. There is a proposed multimodal pragmatic model that is detailed and simplified by the researcher constituting major components: type of data, clusters, a meta-information, contradictions and implicated conclusion. Such a suggested multimodal pragmatic model is derived from Barthes's (1977) and Pastra's (2008) models. Both Barthes's (1977) and Pastra's (2008) models are redundant, superfluous and sometimes confusing. In accordance with the clusters including verbal and visual content under study both Harris (the winner) and Trump (the loser) have the same percentage of clusters. To conclude, Harris, that has the lowest ratio of losing, is more fortunate than both Trump having the lowest percentage of winning and Biden having the highest percentage of losing in presidential race.
Key words: Pragmatic multimodality, American Presidential elections, Pastra's (2008) model.