Update README.md

README.md

@@ -1,31 +1,63 @@
----
-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-*
----
+---
+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.}
+}
+```