README.md

---
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype: string
  - name: id
    dtype: int64
  splits:
  - name: train
    num_bytes: 1148348
    num_examples: 9641
  - name: test
    num_bytes: 317153
    num_examples: 2679
  - name: val
    num_bytes: 125692
    num_examples: 1072
  download_size: 1048892
  dataset_size: 1591193
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
  - split: val
    path: data/val-*
task_categories:
- text-classification
language:
- ru
tags:
- russian
- sentiment_analysis
- social_media
size_categories:
- 1K<n<10K
---

## Disclaimer

This is a reupload of the dataset, which is originally stored on [GitHub](https://github.com/sismetanin/rusentitweet). We only added a `val` split that is 10% of the original `train` split for a convenience. Next the original description is following.

# RuSentiTweet: A Sentiment Analysis Dataset of General Domain Tweets in Russian

This repository contains RuSentiTweet, a sentiment analysis dataset of 13,392 general domain tweets in Russian, which were created within the paper ["RuSentiTweet: A Sentiment Analysis Dataset of General Domain Tweets in Russian"](https://doi.org/10.7717/peerj-cs.1039). RuSentiTweet was manually annotated (moderate inter-rater agreement) using [RuSentiment](https://aclanthology.org/C18-1064/) guidelines into 5 classes: Positive, Neutral, Negative, Speech Act, and Skip. As a source of data, we used [Twitter Stream Grab](https://archive.org/details/twitterstream), a historical collection of tweets obtained from the general Twitter API stream. 

Citation:
```
@article{smetanin2022rusetitweet,
  title = {RuSentiTweet: A Sentiment Analysis Dataset of General Domain Tweets in Russian},
  author = {Sergey Smetanin},
  journal = {PeerJ Computer Science},
  volume = {8},
  pages = {e1039},
  year = {2022},
  doi = {10.7717/peerj-cs.1039},
  publisher = {PeerJ Inc.}
}
```