Update README.md

README.md

@@ -1,64 +1,3 @@
-# GitHub Issue Comments – Hugging Face/datasets Repository
-
-## Dataset Summary
-This dataset contains 4,000 structured GitHub issue comments collected from the huggingface/datasets repository. Each comment includes metadata such as author details, timestamps, reactions and association type. The dataset is ideal for analysing open-source community dynamics, sentiment trends, contributor behaviour and natural language patterns in technical discussions.
-
-## Dataset Structure
-Data Fields
-Column Name	Description
-id	Unique identifier for the comment
-body	Text content of the comment
-created_at	Timestamp when the comment was created
-updated_at	Timestamp when the comment was last updated
-author_association	Role of the commenter (e.g., MEMBER, CONTRIBUTOR, NONE)
-user_login	GitHub username of the commenter
-user_id	Unique GitHub user ID
-user_type	Type of GitHub account (e.g., User, Bot)
-user_site_admin	Boolean indicating if the user is a GitHub site admin
-html_url	Direct URL to the comment on GitHub
-issue_url	API URL of the issue the comment belongs to
-reactions_total_count	Total number of emoji reactions
-reactions_+1 to reactions_eyes	Individual counts for each reaction type (👍, 👎, ❤️, 🎉, etc.)
-performed_via_github_app	GitHub App used to post the comment (if any)
-user_* fields	Additional metadata about the user (avatar, profile URLs, etc.)
-
-## Data Types
-- int64: IDs, reaction counts
-- object: Text, URLs, usernames
-- datetime64[s]: Timestamps
-- bool: Admin flag
-
-## Source
-- Repository: huggingface/datasets
-- API Endpoint: https://api.github.com/repos/huggingface/datasets/issues/comments
-- Collection Method: API calls (per_page=100, page=1–40)
-- License: GitHub content is subject to GitHub Terms of Service
-
-## Intended Uses
-- NLP Tasks: Sentiment analysis, topic modelling, summarisation
-- Community Analytics: Contributor engagement, reaction trends
-- Model Training: Fine-tuning on technical dialogue and bug reporting
-- Feature Engineering: Text length, emoji usage, time-based features, user roles
-
-## Limitations
-- Comments are limited to public issues only.
-- No issue titles or labels are included.
-- performed_via_github_app is always null.
-- Reactions may not reflect full emotional tone.
-
-## Ethical Considerations
-- All data is publicly available via GitHub’s API.
-- Usernames and profile links are included; please respect contributor privacy and avoid misuse.
-
-## Dataset Creation script
-- Data was collected using Python requests library by GitHub REST API:
-- url = "https://api.github.com/repos/huggingface/datasets/issues/comments?per_page=100&page={page}"
-- headers = {"Authorization": f"token {your_token}"}
-- response = requests.get(url, headers=headers)
-- Comments were flattened into a tabular format with 39 columns. Timestamps were parsed, and nested fields (e.g., user, reactions) were expanded.
-
-
-
 ---
 license: apache-2.0
 configs:
@@ -159,4 +98,63 @@ language:
 - en
 size_categories:
 - 1K<n<10K
----
+---
+
+# GitHub Issue Comments – Hugging Face/datasets Repository
+
+## Dataset Summary
+This dataset contains 4,000 structured GitHub issue comments collected from the huggingface/datasets repository. Each comment includes metadata such as author details, timestamps, reactions and association type. The dataset is ideal for analysing open-source community dynamics, sentiment trends, contributor behaviour and natural language patterns in technical discussions.
+
+## Dataset Structure
+Data Fields
+Column Name	Description
+id	Unique identifier for the comment
+body	Text content of the comment
+created_at	Timestamp when the comment was created
+updated_at	Timestamp when the comment was last updated
+author_association	Role of the commenter (e.g., MEMBER, CONTRIBUTOR, NONE)
+user_login	GitHub username of the commenter
+user_id	Unique GitHub user ID
+user_type	Type of GitHub account (e.g., User, Bot)
+user_site_admin	Boolean indicating if the user is a GitHub site admin
+html_url	Direct URL to the comment on GitHub
+issue_url	API URL of the issue the comment belongs to
+reactions_total_count	Total number of emoji reactions
+reactions_+1 to reactions_eyes	Individual counts for each reaction type (👍, 👎, ❤️, 🎉, etc.)
+performed_via_github_app	GitHub App used to post the comment (if any)
+user_* fields	Additional metadata about the user (avatar, profile URLs, etc.)
+
+## Data Types
+- int64: IDs, reaction counts
+- object: Text, URLs, usernames
+- datetime64[s]: Timestamps
+- bool: Admin flag
+
+## Source
+- Repository: huggingface/datasets
+- API Endpoint: https://api.github.com/repos/huggingface/datasets/issues/comments
+- Collection Method: API calls (per_page=100, page=1–40)
+- License: GitHub content is subject to GitHub Terms of Service
+
+## Intended Uses
+- NLP Tasks: Sentiment analysis, topic modelling, summarisation
+- Community Analytics: Contributor engagement, reaction trends
+- Model Training: Fine-tuning on technical dialogue and bug reporting
+- Feature Engineering: Text length, emoji usage, time-based features, user roles
+
+## Limitations
+- Comments are limited to public issues only.
+- No issue titles or labels are included.
+- performed_via_github_app is always null.
+- Reactions may not reflect full emotional tone.
+
+## Ethical Considerations
+- All data is publicly available via GitHub’s API.
+- Usernames and profile links are included; please respect contributor privacy and avoid misuse.
+
+## Dataset Creation script
+- Data was collected using Python requests library by GitHub REST API:
+- url = "https://api.github.com/repos/huggingface/datasets/issues/comments?per_page=100&page={page}"
+- headers = {"Authorization": f"token {your_token}"}
+- response = requests.get(url, headers=headers)
+- Comments were flattened into a tabular format with 39 columns. Timestamps were parsed, and nested fields (e.g., user, reactions) were expanded.