ANNOTATION AND SENTIMENT ANALYSIS OF TWEETS RELATED TO THE POLITICAL SCENE OF THE REPUBLIC OF SERBIA

Authors

  • Владимир Буђен Autor

DOI:

https://doi.org/10.24867/23BE04Budjen

Keywords:

tweeter, politics, artificial intelligence, sentiment, BERT

Abstract

This paper describes tweet sentiment analysis and the development of a tool for placing tweet authors on a political map. The purpose of this system is to assist its users in political elections. BERTić model is used for tweet sentiment analysis. Sentiment and tweet’s theme are used as inputs for SVM and Random-forest, which are used for user polarization.

References

[1] J. D. M.-W. C. K. L. K. Toutanova, „BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding“.
[2] B. G. J. R. A. F. F. M. Michael D. Conover, Predicting the Political Alignment of Twitter Users.
[3] E. L.-G. Jhon Adrian Ceron-Guzman, A Sentiment Analysis System of Spanish Tweets and Its Application in Colombia 2014 Presidential Election.
[4] D. L. Nikola Ljubešić, „BERTić - The Transformer Language Model for Bosnian, Croatian, Montenegrin and Serbian“.
[5] „EMBEDDIA/bertic-tweetsentimen,“ [На мрежи]. Available: https://huggingface.co/EMBEDDIA/bertic-tweetsentimen.
[6] „SrbAi,“ [На мрежи]. Available: https://github.com/Serbian-AI-Society/SrbAI.
[7] „Scikit-learn,“ [На мрежи]. Available: https://scikit-learn.org/stable/.
[8] М. Кнежевић, „Позиционирање корисника друштвене мреже Twitter на мапи политичког спектра помоћу корисничких твитова“.

Published

2023-07-07

Issue

Section

Electrotechnical and Computer Engineering