Multimodal Analysis about the America’s Mascots Comics on the Shen Comics Instagram Account (A Language Learning Media)

Authors

  • J Juanda English Department, Faculty of Letters, Universitas Komputer Indonesia, Indonesia

DOI:

https://doi.org/10.34010/icobest.v1i.102

Keywords:

Multimodal Analysis, Comics, Language learning media

Abstract

The research entitled Multimodal Analysis of comics about America’s Mascots in Shen Comics Instagram Account. The research has purposes to analyze the interpretation language that is appear in the comics on Shen Comics Instagram account. The research used the theories of multimodality analysis by Kress and Leeuwen. Theory of comic by Franz and Meier. The method of this research is a descriptive-analytic method. The analysis is based on an investigation of an event, essay, or act for know the real situation. This research is done by describing the data and information obtained, the writer used scientific journals, the sources are downloaded from the internet, as well as through visual media such as visual image from the Shen Comics Instagram account and at the final stage will be the conclusion of the analysis results. There are found that the interpretation language that is appear on comic in Shen Comics Instagram account is about local wisdom by illustrating the big four cities in America including San Fransisco, Los Angeles, New York and Boston. This analysis can be used for language learning purposes such as semiotic studies.The suggestions of the research are it would be better for the reader to understand the meaning of the comic, it will help the reader to be more completely understand the message or even the entertainment of the comic. Therefore, the reader will be able to acknowledge the information without any ambiguity occurs.

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Published

2023-03-10

How to Cite

Juanda, J. (2023). Multimodal Analysis about the America’s Mascots Comics on the Shen Comics Instagram Account (A Language Learning Media). Proceeding of International Conference on Business, Economics, Social Sciences, and Humanities, 3, 618-624. https://doi.org/10.34010/icobest.v1i.102