Sentiment Analysis for the data from the RuSentNE-2023

Sentiment analysis in relations to the named entities from the data from the RuSentNE-2023 competition using the RuBERT model, it's modifications, and various techniques.

Sentiment analysis dataset

For model training the data from the RuSentNE-2023 repository was used.

Usage

• The first option is to open and run the notebook /notebooks/sentiment_analysis.ipynb with comments and visualizations in Kaggle or Google Colab.

• The second option is cloning the repo, installing the needed requirements, and working locally:

git clone https://github.com/RadyaSRN/sentiment-analysis-RuSentNE-2023.git
cd sentiment-analysis-RuSentNE-2023
conda create -n sentanalysis python=3.10
conda activate sentanalysis
pip install -r requirements.txt