|
|
---
|
|
|
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-*
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|
|
task_categories:
|
|
|
- text-classification
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|
|
language:
|
|
|
- ru
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|
|
tags:
|
|
|
- russian
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|
|
- sentiment_analysis
|
|
|
- social_media
|
|
|
size_categories:
|
|
|
- 1K<n<10K
|
|
|
---
|
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## Disclaimer |
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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. |
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# RuSentiTweet: A Sentiment Analysis Dataset of General Domain Tweets in Russian |
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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. |
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Citation: |
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|
``` |
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|
@article{smetanin2022rusetitweet, |
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title = {RuSentiTweet: A Sentiment Analysis Dataset of General Domain Tweets in Russian}, |
|
|
author = {Sergey Smetanin}, |
|
|
journal = {PeerJ Computer Science}, |
|
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volume = {8}, |
|
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pages = {e1039}, |
|
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year = {2022}, |
|
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doi = {10.7717/peerj-cs.1039}, |
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publisher = {PeerJ Inc.} |
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|
} |
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|
``` |
