Identifying Representative Images for Events Description Using Machine Learning

Marcos Soares de Sousa, Raimundo C. S. Vasconcelos

2024

Abstract

The use of social networks to record events – disasters, demonstrations, parties – has grown a lot and has begun to receive attention in recent years. Existing research focuses primarily on analyzing text-based messages from social media platforms such as Twitter. Images, photos and other media are increasingly used and can provide valuable information to enhance the understanding of an event and can be used as indicators of relevance. This work explores the Twitter social media platform, based on image and text in the case of the demonstrations that took place in Brazil on September 7, 2021, as a result of the Independence celebrations. This work uses machine learning techniques (VGG-16, VGG-19, ResNet50v2 and InceptionResNetv2) for finding relevant Twitter images. The results show that the existence of an image within a social media message can serve as a high probability indicator of relevant content. An extensive experimental evaluation was carried out and demonstrated that high efficiency gains can be obtained compared to state-of-the-art methods.

Paper Citation

in Harvard Style

Soares de Sousa M. and C. S. Vasconcelos R. (2024). Identifying Representative Images for Events Description Using Machine Learning. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 409-416. DOI: 10.5220/0012354000003660

in Bibtex Style

@conference{visapp24,
author={Marcos Soares de Sousa and Raimundo C. S. Vasconcelos},
title={Identifying Representative Images for Events Description Using Machine Learning},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={409-416},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012354000003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Identifying Representative Images for Events Description Using Machine Learning
SN - 978-989-758-679-8
AU - Soares de Sousa M.
AU - C. S. Vasconcelos R.
PY - 2024
SP - 409
EP - 416
DO - 10.5220/0012354000003660
PB - SciTePress