Update README.md

README.md

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   - split: train
     path: data/train-*
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+# README: Dataset Cleanup and Processing Journal
+
+### Dataset Source
+- **Original Source**: [MuscariMedia/reddittest113024](https://huggingface.co/datasets/MuscariMedia/reddittest113024)
+- **Dataset Details**: Contains 12,000 Reddit posts.
+
+### Samplyling 
+1. **Challenges Identified**
+Uneven Data Distribution:
+
+- Months: October and November have similar data amounts, but December has much less.
+- Weeks: Significant differences between weeks (e.g., Weeks 42-48 have much more data than Weeks 41, 49, and 50).
+- Weekdays vs. Weekends: Weekdays have more data than weekends. Hours: Peaks during certain hours (10 AM - 1 PM, smaller peak 5 PM - 7 PM).
+- Non-Numerical Data: Aggregation methods like mean or sum are not applicable.
+- Score Interpretation: The score distribution is highly skewed to the right (positive skewness). A small number of titles have very high scores, while the majority have low scores. Median (15) is much lower than the mean (~1,142.78), indicating that most scores are below the mean.
+
+2. **Sampling Strategy**
+We are gonna use multi-stage stratified sampling approach with proportional allocation, combined with oversampling in underrepresented strata. This method involves:
+
+  a. Stratification Levels:
+    - Level 1: Months (October, November, December)
+    - Level 2: Weeks within each month
+    - Level 3: Weekdays vs. Weekends
+    - Level 4: Hourly intervals
+  b. Alternative Sampling Strategy
+    - To balance the focus on high-scoring titles while maintaining representativeness, consider the following modified approach:
+      Stratified Sampling with Score-Based Selection
+    - Method:
+      Within each stratum, sort the data by score in descending order.
+      Select the top `n` titles based on score and randomly sample additional titles.
+    
+3. **Potential Biases and Risks**:
+  - Selection Bias: Overrepresentation of high scores, underrepresentation of diversity.
+  - Temporal Bias: Skewed comparisons across time periods.
+
+### Cleanup and Encoding Tasks
+1. **Title Text Cleanup**:
+   - Corrected spelling errors in post titles (e.g., "Presidential Eelction" → "Presidential Election").
+   - Removed artifacts and symbols appearing in text strings.
+   - Reformatted text for readability using proper quotation marks.
+     
+2. **Ecode True/False string**
+For columns:
+```
+is_crosspostable
+can_gild
+author_patreon_flair
+is_video
+stickied
+is_original_content
+is_self
+pinned
+no_follow
+can_mod_post
+spoiler
+allow_live_comments
+archived
+is_reddit_media_domain
+author_premium
+locked
+media_only
+is_created_from_ads_ui
+```
+
+3. **Encode b'True/False' formate**:
+Handles cases like b'True', b"b'False'", b'true' etc.
+For columns
+```
+over_18
+is_meta
+is_robot_indexable
+quarantine
+send_replies
+hide_score
+contest_mode
+```
+4. **Encode b'int' formate**:
+For columns:
+```
+thumbnail_width
+num_comments
+pwls
+```
+
+5. **permalink**:
+The extra backslashes (\) you're seeing in fields like **permalink**, **thumbnail**, and **url** are escape characters that appear in the JSON representation of the data.
+This is a common source of confusion when dealing with JSON strings that contain special characters like forward slashes (/).
+
+The backslashes are not part of the actual string content; they are just there to ensure that the JSON is correctly formatted and can be parsed without errors.
+For better tracking the link, I added the ```"https://www.reddit.com"``` at the front of the **"permalink"**.
+
+
+### Relevance Analysis
+- **Model**: `gpt-4o-mini`
+- **Task**: Evaluated the relevance of post titles to the US presidential elections.
+  - Added a new column `us_presidential_election`:
+    - `1`: Title related to US presidential elections.
+    - `0`: Title not related.
+
+### Topic Classification
+- **Model**: `gpt-4o-mini`
+- Added a `topics` column:
+    - Value format: Comma-separated list of topics (e.g., `"economy, democracy"`).
+- **Possible topics**: 
+    ```
+     'LGBTQ',
+     'Social Security',
+     'abortion',
+     'age',
+     'child care',
+     'climate change',
+     'conspiracy',
+     'crime',
+     'democracy',
+     'discrimination',
+     'disinformation',
+     'drug policy',
+     'economy',
+     'education',
+     'election',
+     'environment',
+     'equity',
+     'ethics',
+     'foreign relations',
+     'freedom of speech',
+     'gender',
+     'health',
+     'human rights',
+     'immigrant',
+     'justice',
+     'media',
+     'opportunity',
+     'political parties',
+     'race',
+     'religion',
+     'veterans',
+     'violence',
+     'voting rights',
+     'youth'
+    ```
+
+### Dataset Restructuring
+- Converted the dataset into **JSON format** with the following structure:
+  - **Post_Metadata**:
+    - `id`, `permalink`, `removed_by_category`, `created_est`, `subreddit_subscribers`, `suggested_sort`, `is_robot_indexable`
+  - **Author_Data**:
+    - `author`, `author_full_name`, `upvote_ratio`, `author_flair_text`
+  - **Post_Info**:
+    - `title`, `url`, `domain`, `thumbnail`, `over_18`, `send_replies`, `is_original_content`
+  - **Sharing_Info**:
+    - `score`, `upvote_ratio`, `num_comments`, `num_crossposts`
+  - **Additional Fields**:
+    - `us_presidential_election`, `topics`