Crowdsourced Explanations for Humorous Internet Memes Based on Linguistic Theories

Authors

  • Chi-Chin Lin National Taiwan University
  • Yi-Ching Huang National Taiwan University
  • Jane Yung-jen Hsu National Taiwan University

Keywords:

computational humor recognition, crowdsourcing, Internet memes, template-based explanations

Abstract

Humorous images can be seen in many social media websites. However, newcomers to these websites often have trouble fitting in because the community subculture is usually implicit. Among all the types of humorous images, Internet memes are relatively hard for newcomers to understand. In this work, we develop a system that leverages crowdsourcing techniques to generate explanations for memes. We claim that people who are not familiar with Internet meme subculture can still quickly pick up the gist of the memes by reading the explanations. Our template-based explanations illustrate the incongruity between normal situations and the punchlines in jokes. The explanations can be produced by completing the two proposed human task processes. Experimental results suggest that the explanations produced by our system greatly help newcomers to understand unfamiliar memes. For further research, it is possible to employ our explanation generation system to improve computational humanities.

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Published

2014-09-05

How to Cite

Lin, C.-C., Huang, Y.-C., & Hsu, J. Y.- jen. (2014). Crowdsourced Explanations for Humorous Internet Memes Based on Linguistic Theories. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2(1). Retrieved from https://ojs.aaai.org/index.php/HCOMP/article/view/13169