The Twitter-Lex Sentiment Analysis System

Sergiu Limboi, Laura Dioşan

2022

Abstract

Twitter Sentiment Analysis is demanding due to the freestyle way people express their opinions and feelings. Using only the preprocessed text from a dataset does not bring enough value to the process. Therefore, there is a need to define and mine different and complex features to detect hidden information from a tweet. The proposed Twitter-Lex Sentiment Analysis system combines lexicon features with Twitter-specific ones to improve the classification performance. Therefore, several features are considered for the Sentiment Analysis process: only textual input from a tweet, hash-tags, and some flavors that combine them with the feature defined based on the result produced by a lexicon. So, the Vader lexicon is used to determine the sentiment of a tweet. This output will be appended to the four perspectives we defined, considering the features offered by Twitter. The experimental results reveal that our system, which focuses on the role of features in a classification process, outperforms the baseline approach (use of original tweets) and provides good value to new directions and improvements.

Paper Citation

in Harvard Style

Limboi S. and Dioşan L. (2022). The Twitter-Lex Sentiment Analysis System. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 1: KDIR; ISBN 978-989-758-614-9, SciTePress, pages 180-187. DOI: 10.5220/0011379900003335

in Bibtex Style

@conference{kdir22,
author={Sergiu Limboi and Laura Dioşan},
title={The Twitter-Lex Sentiment Analysis System},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 1: KDIR},
year={2022},
pages={180-187},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011379900003335},
isbn={978-989-758-614-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 1: KDIR
TI - The Twitter-Lex Sentiment Analysis System
SN - 978-989-758-614-9
AU - Limboi S.
AU - Dioşan L.
PY - 2022
SP - 180
EP - 187
DO - 10.5220/0011379900003335
PB - SciTePress