IJCAI 2022poster9 citations

Towards Contextually Sensitive Analysis of Memes: Meme Genealogy and Knowledge Base

Victoria Sherratt

Abstract

As online communication grows, memes have continued to evolve and circulate as succinct multimodal forms of communication. However, computational approaches applied to meme-related tasks lack the same depth and contextual sensitivity of non-computational approaches and struggle to interpret intra-modal dynamics and referentiality. This research proposes to a ‘meme genealogy’ of key features and relationships between memes to inform a knowledge base constructed from meme-specific online sources and embed connotative meaning or contextual information in memes. The proposed methods provide a basis to train contextually sensitive computational models for analysing memes and applications in semi-automated meme annotation.

Computer Vision (CV): GeneralSpeech & Natural Language Processing (SNLP): GeneralKnowledge Representation and Reasoning (KRR): General
BibTeX
@inproceedings{ijcai2022p838,
  title     = {Towards Contextually Sensitive Analysis of Memes: Meme Genealogy and Knowledge Base},
  author    = {Sherratt, Victoria},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Lud De Raedt},
  pages     = {5871--5872},
  year      = {2022},
  month     = {7},
  note      = {Doctoral Consortium},
  doi       = {10.24963/ijcai.2022/838},
  url       = {https://doi.org/10.24963/ijcai.2022/838},
}
Towards Contextually Sensitive Analysis of Memes: Meme Genealogy and Knowledge Base · IJCAI 2022