IJCAI 2022poster9 citations
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.
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},
}