Extract-Transform-Load Process for Recognizing Sentiment from User-Generated Text on Social Media

Afef Walha, Afef Walha, Faiza Ghozzi, Faiza Ghozzi, Faiez Gargouri, Faiez Gargouri

2024

Abstract

In today’s world, business intelligence systems must incorporate opinion mining into their decision-making process. Sentiment analysis of user-generated content on social media has gained significant attention in recent years. This method collects user opinions, feelings, and attitudes toward a topic of interest and helps determine whether their sentiment is positive, neutral, or negative. This paper addresses text classification in sentiment analysis and presents a solution to the Extract-Transform-Load (ETL) process based on a lexicon approach. This process involves gathering media clips, converting them into sentiments, and loading them into a social data warehouse. We provide generic and customizable models to aid designers in integrating pre-processing techniques and sentiment analysis into the ETL process. By formalizing new ETL concepts, designers can create a reliable conceptual design for any ETL process related to opinion data integration from social media.

Paper Citation

in Harvard Style

Walha A., Ghozzi F. and Gargouri F. (2024). Extract-Transform-Load Process for Recognizing Sentiment from User-Generated Text on Social Media. In Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE; ISBN 978-989-758-696-5, SciTePress, pages 641-648. DOI: 10.5220/0012706100003687

in Bibtex Style

@conference{enase24,
author={Afef Walha and Faiza Ghozzi and Faiez Gargouri},
title={Extract-Transform-Load Process for Recognizing Sentiment from User-Generated Text on Social Media},
booktitle={Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE},
year={2024},
pages={641-648},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012706100003687},
isbn={978-989-758-696-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE
TI - Extract-Transform-Load Process for Recognizing Sentiment from User-Generated Text on Social Media
SN - 978-989-758-696-5
AU - Walha A.
AU - Ghozzi F.
AU - Gargouri F.
PY - 2024
SP - 641
EP - 648
DO - 10.5220/0012706100003687
PB - SciTePress