README.md

metadata

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. 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". RuSentiTweet was manually annotated (moderate inter-rater agreement) using RuSentiment guidelines into 5 classes: Positive, Neutral, Negative, Speech Act, and Skip. As a source of data, we used Twitter Stream Grab, 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.}
}