# Investigating the Effect of Emoji in Opinion Classification of Uzbek Movie Review Comments

arXiv: https://arxiv.org/abs/2008.00482 · HTML: https://mlsanity.com/paper/2008.00482/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Aug 2020.

## Built on by (most cited first, 5 of 5)

- [SimRelUz: Similarity and Relatedness scores as a Semantic Evaluation dataset for Uzbek language](https://mlsanity.com/paper/2205.06072/) (2022)
- [A machine transliteration tool between Uzbek alphabets](https://mlsanity.com/paper/2205.09578/) (2022)
- [Comparison of Machine Learning for Sentiment Analysis in Detecting Anxiety Based on Social Media Data](https://mlsanity.com/paper/2101.06353/) (2021)
- [Uzbek Sentiment Analysis based on local Restaurant Reviews](https://mlsanity.com/paper/2205.15930/) (2022)
- [Creating a morphological and syntactic tagged corpus for the Uzbek language](https://mlsanity.com/paper/2210.15234/) (2022)

## Abstract (arXiv)

Opinion mining on social media posts has become more and more popular. Users often express their opinion on a topic not only with words but they also use image symbols such as emoticons and emoji. In this paper, we investigate the effect of emoji-based features in opinion classification of Uzbek texts, and more specifically movie review comments from YouTube. Several classification algorithms are tested, and feature ranking is performed to evaluate the discriminative ability of the emoji-based features.