This dataset contains posts and comments from the VK community "Совет Кинеш" (Sovet Kinesh), a Tatar-language community focused on cultural, social, and educational content. The data was collected to support NLP research and development for the Tatar language, particularly for tasks such as text classification, sentiment analysis, language modeling, and social media analysis.

Curated by: TatarNLPWorld
Language(s): Tatar (mainly), Russian (some code-switching)
License: Apache 2.0

Dataset Sources

Repository: TatarNLPWorld/sovet_kinesh-vk

Uses

Direct Use

This dataset can be used for:

Text classification (topic classification, sentiment analysis)
Language modeling for Tatar
Social media analysis
Discourse analysis
Code-switching detection
Comment moderation research
Cultural content analysis
Educational text mining

Out-of-Scope Use

This dataset should not be used for:

Identifying individual users
Surveillance or profiling
Any purpose that violates VK's terms of service

How to Use

from datasets import load_dataset

# Load posts
posts = load_dataset("TatarNLPWorld/sovet_kinesh-vk", "posts", split="full")
posts_sample = load_dataset("TatarNLPWorld/sovet_kinesh-vk", "posts", split="sample")

# Load comments
comments = load_dataset("TatarNLPWorld/sovet_kinesh-vk", "comments", split="full")
comments_sample = load_dataset("TatarNLPWorld/sovet_kinesh-vk", "comments", split="sample")

# Convert to pandas for analysis
posts_df = posts.to_pandas()
comments_df = comments.to_pandas()

# Merge posts and comments
merged = posts_df.merge(comments_df, on='post_id', how='left')

# Example: Show first few rows
print(posts_df.head())
print(comments_df.head())

# Example: Get basic statistics
print(f"Total posts: {len(posts_df)}")
print(f"Total comments: {len(comments_df)}")
print(f"Average post length: {posts_df['content'].str.len().mean():.1f} characters")
print(f"Average comment length: {comments_df['content'].str.len().mean():.1f} characters")

Dataset Structure

Data Instances

Posts:

{
  "post_id": 123456,
  "owner_id": -73028796,
  "url": "https://vk.com/wall-73028796_123456",
  "date": "2023-01-01 12:00:00",
  "content": "Post text in Tatar...",
  "author_id": -73028796,
  "likes_count": 23,
  "comments_count": 29,
  "reposts_count": 9,
  "views_count": 8890
}

Comments:

{
  "comment_id": 654321,
  "post_id": 123456,
  "owner_id": -73028796,
  "parent_comment_id": 0,
  "from_id": 419553410,
  "date": "2023-01-01 13:00:00",
  "content": "Comment text...",
  "likes_count": 3
}

Data Fields

Posts:

post_id: Unique identifier for the post
owner_id: ID of the community/page that owns the post (-73028796 for this community)
url: Direct URL to the post
date: Post creation timestamp (UTC)
content: Text content of the post
author_id: ID of the post author
likes_count: Number of likes on the post
comments_count: Number of comments on the post
reposts_count: Number of reposts
views_count: Number of views

Comments:

comment_id: Unique identifier for the comment
post_id: ID of the post this comment belongs to
owner_id: ID of the community/page
parent_comment_id: ID of parent comment (always 0 in this dataset, no nested replies)
from_id: ID of the comment author
date: Comment creation timestamp (UTC)
content: Text content of the comment
likes_count: Number of likes on the comment

Data Splits

The dataset is split into two configurations:

posts: Contains only posts
comments: Contains only comments

Each configuration has two splits:

full: Complete dataset
sample: 1000 random examples for quick experimentation

Dataset Creation

Curation Rationale

The dataset was created to address the lack of publicly available Tatar language social media data for NLP research. The Sovet Kinesh community was chosen as it actively publishes content in Tatar and focuses on cultural, social, and educational topics relevant to the Tatar-speaking community.

Source Data

Data Collection and Processing

Data was collected from the VK community "Совет Кинеш" (https://vk.com/sovet_kinesh) using the official VK API. The collection process:

All posts from the community were collected
All comments on those posts were collected
Data was cleaned and formatted into CSV format
Personal identifiers were preserved for research purposes but should be handled responsibly

Who are the source data producers?

The data was produced by members of the Sovet Kinesh VK community who post and comment in Tatar and Russian. The community focuses on Tatar culture, social issues, and educational content.

Annotations

The dataset does not contain manual annotations. All data is raw text from VK with associated metadata.

Personal and Sensitive Information

The dataset contains:

User IDs (VK internal identifiers)
Public comments and posts
Public interaction counts (likes, reposts, views)

No private messages, email addresses, phone numbers, or other personally identifiable information is included. However, user IDs could potentially be used to cross-reference with other public data. Researchers should handle this data responsibly and not attempt to de-anonymize users.

Bias, Risks, and Limitations

Known Biases

Community bias: Data comes from a single VK community, which may not represent all Tatar speakers
Platform bias: Social media language differs from formal written or spoken language
Topic bias: Content reflects the interests of the Sovet Kinesh community (cultural, social, educational)
Temporal bias: Posts span from 2022 to 2026, with possible topical shifts over time

Content Limitations

Code-switching between Tatar and Russian is common
Contains internet slang, emoji, and informal language
May contain political or sensitive discussions
No nested replies (all comments are top-level)

Recommendations

Users should:

Be aware of the dataset's biases when training models
Not use for demographic profiling
Consider additional filtering for specific tasks
Handle user IDs with care and respect user privacy

Dataset Statistics

Posts Statistics

Total posts: 10,205
Date range: 2022-03-14 to 2026-03-10 (1,456 days)
Total characters: 2,222,766
Average post length: 218 characters
Total likes: 231,745 (avg 22.7 per post)
Total comments: 297,588 (avg 29.2 per post)
Total reposts: 92,054 (avg 9.0 per post)
Total views: 90,723,870 (avg 8,890 per post)
Posts with comments: 9,751 (95.6%)
Posts without comments: 454 (4.4%)
Posts with likes: 10,155 (99.5%)
Posts without likes: 50 (0.5%)

Comments Statistics

Total comments: 137,988
Total characters: 17,104,354
Average comment length: 124 characters
Total likes on comments: 368,230 (avg 2.7 per comment)
Unique comment authors: 137,514 (99.66% of comments are from unique authors)
Top-level comments: 137,988 (100%, no nested replies)
Comments with likes: 83,187 (60.3%)
Comments without likes: 54,801 (39.7%)

Overall Dataset

Total records: 148,193
Total characters: 19,327,120
Total size: ~42.5 MB (raw CSV)
Total interactions (likes + comments + reposts): 989,617

Citation

If you use this dataset in your research, please cite:

@dataset{sovet-kinesh-vk-2026,
  title = {Sovet Kinesh VK Dataset: Tatar Language Social Media Posts and Comments},
  author = {Arabov Mullosharaf Kurbonovich},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/TatarNLPWorld/sovet-kinesh-vk}
}

Dataset Card Authors

TatarNLPWorld Team

Dataset Card Contact

For questions or feedback, please contact through the Hugging Face repository issues page.

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