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Age and gender differences in meme humor: a multimodal variationist mixed-method approach

  • Inke Du Bois ORCID logo EMAIL logo
Published/Copyright: October 11, 2024

Abstract

Digital humor expressed through memes plays a vital role in facilitating social interaction in online environments. This paper reports on age and gender-related differences in multimodal digital meme humor from users aged 14 to 93. Its aim is to investigate how visual and textual elements, psychological humor types and digital humor types vary among smartphone users of different age and gender groups. The multimodal corpus was compiled from memes that were shared by 250 BA English and senior citizen students at a German university and their relatives and friends. The memes were annotated with the Covid-19 topic (e.g. lockdown, mask requirement, vaccination) and the sources of visual origin (e.g. cartoon characters, animals, politicians). Also, a previously non-multimodal psychological humor framework (Martin, Rod A., Patricia Puhlik-Doris, Gwen Larsen, Jeanette Gray & Kelly Weir. 2003. Individual differences in uses of humor and their relation to psychological well-being: Development of the Humor Styles Questionnaire. Journal of Research in Personality 37(1) 48–75) was applied to the memes. To determine the linguistic multimodal digital humor types, Vásquez, C. 2019. Language, creativity and humour online. London). Terminology was employed for annotation. The statistical analysis reveals only slight gender differences concerning all variables. Significant differences were found concerning both multimodal humor frameworks, language usage, canvas and humor themes across all age groups. The interconnectedness of the codes is captured in a qualitative analysis of select memes to underscore the semiotic dynamics of multimodal humor.


Corresponding author: Inke Du Bois, University of Bremen, Bremen, Germany, E-mail:

Funding source: Department of Language and Literature, Bremen University

Acknowledgments

This research would not have been possible without the BA English speaking cultures students and senior citizen students of Bremen University who submitted the memes as research participants. It would have not been possible without my research assistants, the MA English speaking culture graduate students who helped with coding, annotating and discussing the data in weekly meetings: Hande Akin, Ekaterina Buchkinskaya, Megan Dwinger, Hasan Mir Sabbir, Jesco Oentrich, Svetlana Smolina, Yooju Sun, Shuting Le (China), Amal Johns (India/Malayam), Chadi Allam (Lebanon/Arabic), Hasan Mir Sabbir (Bangladesh/Bangla) Alina Azarteva (Russia). Kate Stollmann gave helpful comments on language issues. I would also like to thank Julian Du Bois whose expertise in Generation Z memes were the inducement to start the data collection for this project with my students. I am grateful for John Bateman’s great expertise and support with some of the statistics. Further, I would like to thank Sigrid Norris for her inspiring work on multimodal communication. Finally, I would like to thank the editors and reviewers for their helpful comments. Mistakes and misinterpretations of any positions presented remain solely the responsibility of the author.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author designed the research project, conducted the table calculations, the descriptive statistical analyses and wrote the research article. The data was curated and coded by the research assistants and the author.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of Interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

  6. Research funding: Licenses for the MAXQDA 2020 software were funded by dean Marcus Callies of the Department of Languages and Literatures, Bremen University, Germany.

  7. Data availability: Not applicable.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/mc-2024-0051).


Received: 2024-05-07
Accepted: 2024-07-22
Published Online: 2024-10-11

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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