Towards Contextually Sensitive Analysis of Memes: Meme Genealogy and Knowledge Base
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.
Cite
Text
Sherratt. "Towards Contextually Sensitive Analysis of Memes: Meme Genealogy and Knowledge Base." International Joint Conference on Artificial Intelligence, 2022. doi:10.24963/IJCAI.2022/838Markdown
[Sherratt. "Towards Contextually Sensitive Analysis of Memes: Meme Genealogy and Knowledge Base." International Joint Conference on Artificial Intelligence, 2022.](https://mlanthology.org/ijcai/2022/sherratt2022ijcai-contextually/) doi:10.24963/IJCAI.2022/838BibTeX
@inproceedings{sherratt2022ijcai-contextually,
title = {{Towards Contextually Sensitive Analysis of Memes: Meme Genealogy and Knowledge Base}},
author = {Sherratt, Victoria},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2022},
pages = {5871-5872},
doi = {10.24963/IJCAI.2022/838},
url = {https://mlanthology.org/ijcai/2022/sherratt2022ijcai-contextually/}
}