Update README.md

README.md

@@ -36,18 +36,35 @@ configs:
 # Top Reddit Posts Daily
 
 ## Dataset Summary
-A continuously‐updated collection of daily “top” posts and their top comments from configurable subreddits, scraped via PRAW (the Reddit API). Each day’s data is stored as a separate Parquet file under `data_raw/{YYYY‑MM‑DD}.parquet`.
 
-- **Source:** Reddit (via PRAW)  
-- **Frequency:** Daily  
-- **Data files:** Parquet (`.parquet`)  
-- **Total records per day:** Varies by subreddit and limits  
+A continuously-updated snapshot of public Reddit discourse on AI news. Each night a GitHub Actions cron job
 
-Currently configured to pull top posts from r/Apple, r/Android, and r/GooglePixel
+1. **Scrapes** new submissions from a configurable list of subreddits (→ `data_raw/`)
+2. **Classifies** each post with a DistilBERT sentiment model served on Replicate (→ `data_scored/`)
+3. **Summarises** daily trends for lightweight front-end consumption (→ `daily_summary/`)
 
-Source code https://github.com/halstonblim/reddit_scraper
+The result is an easy-to-query, time-stamped record of Reddit sentiment that can be used for NLP research, social-media trend analysis, or as a teaching dataset for end-to-end MLOps.
 
-## Supported Tasks and Leaderboards
+Source code https://github.com/halstonblim/reddit_sentiment_pipeline
+
+Currently configured to scrape only the top daily posts and comments to respect rate limits
+```
+subreddits:
+  - name: artificial
+    post_limit: 100
+    comment_limit: 10
+  - name: LocalLLaMA
+    post_limit: 100
+    comment_limit: 10
+  - name: singularity
+    post_limit: 100
+    comment_limit: 10
+  - name: OpenAI
+    post_limit: 100
+    comment_limit: 10
+```
+
+## Supported Tasks
 This dataset can be used for:
 - Text classification (e.g., sentiment analysis)
 - Topic modeling
@@ -56,16 +73,21 @@ This dataset can be used for:
 
 
 ## Languages
-- English (primary; non‑English text may appear depending on subreddit content)
+- English, no filtering is currently done on the raw text
 
 ## Dataset Structure
 
 ```
 hblim/top_reddit_posts_daily/
-└── data_raw/
-    ├── 2025‑04‑15.parquet
-    ├── 2025‑04‑16.parquet
+└── data_raw/                     # contains raw data scraped from reddit
+    ├── 2025‑05‑01.parquet
+    ├── 2025‑05‑01.parquet
     └── …
+└── data_scored/                  # contains same rows as raw data but with sentiment scores
+    ├── 2025‑05‑01.parquet
+    ├── 2025‑05‑01.parquet
+    └── …
+└── subreddit_daily_summary.csv/  # contains daily summaries of sentiment averages grouped by (day, subreddit)
 ```
 
 ### Data Fields
@@ -96,23 +118,15 @@ Example entry:
 
 
 ## Data Splits
-There are no explicit train/test splits. Data is organized by date under the `data_raw/` folder.
+There are no explicit train/test splits. Data is organized by date under the `data_raw/` or `data_scored/` folder.
 
 ## Dataset Creation
 
-1. **Curation**  
    - A Python script (`scrape.py`) runs daily, fetching the top N posts and top M comments per subreddit.  
    - Posts are retrieved via PRAW’s `subreddit.top(time_filter="day")`.  
    - Data is de‑duplicated against the previous day’s `post_id` values.  
    - Stored as Parquet under `data_raw/{YYYY‑MM‑DD}.parquet`.
 
-2. **Source Data**  
-   - Reddit’s public API (PRAW), subject to Reddit rate limits and API terms.
-
-3. **Recommendations**  
-   - Respect Reddit’s API rate limits and community rules.  
-   - Consider throttling or caching for large‑scale usage.
-
 ## License
 This dataset is released under the [MIT License](https://opensource.org/licenses/MIT).
 
@@ -177,5 +191,4 @@ print(f"Total records across {len(dfs)} days: {len(df_all)}")
 
 ## Limitations & Ethics
 - **Bias:** Data reflects Reddit’s user base and community norms, which may not generalize.  
-- **Rate Limits:** Excessive scraping may violate Reddit API terms.  
 - **Privacy:** Only public content is collected; no personally identifiable information is stored.