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---
license: cc-by-4.0
task_categories:
- feature-extraction
language:
- en
tags:
- finance
- reddit
- social-media
- sentiment-analysis
- apple
- tesla
- microsoft
pretty_name: Reddit Finance Sample Dataset (Apple/Tesla/Microsoft)
size_categories:
- 10K<n<100K
---
# Reddit Finance Comments Dataset (Apple, Tesla, Microsoft)
This dataset contains 12046 comments collected from 20 finance-related subreddits
( "stocks", "wallstreetbets", "investing", "StockMarket", "options", "RobinHood",
"pennystocks", "SecurityAnalysis", "personalfinance", "Dividends", "CryptoCurrency",
"CryptoMarkets", "ETFs", "FinancialIndependence", "ValueInvesting", "quant",
"algotrading", "forex", "economy", "Superstonk", "spacs", "financialplanning" )
via the Reddit API using the keywords **Apple**, **Tesla**, and **Microsoft**.
## About This Dataset
This is a **small-scale, beginner-friendly dataset** intended mainly for testing, prototyping, and educational purposes.
It serves as a minimal, ready-to-use sample for anyone who wants to experiment with Reddit finance discussions.
**Easy to Extend:**
The provided data collection pipeline (see [**emilpartow/financial-sentiment-pipeline**](https://github.com/emilpartow/financial-sentiment-pipeline)) makes it simple to expand the dataset with more comments, different time frames, additional companies, or other subreddits as needed.
If you need a larger or customized dataset, you can easily adapt and rerun the pipeline to collect more data for your own use case.
## Dataset Overview
Each row in the dataset contains metadata and content for a Reddit comment or post, with the following columns:
- `id`: Reddit comment or post ID
- `title`: Title of the post (if available)
- `text`: Body text of the comment or post
- `created_utc`: Timestamp in UTC
- `created_datetime`: Datetime (ISO format)
- `author`: Reddit username (anonymized or pseudonymous)
- `score`: Reddit score (upvotes minus downvotes)
- `num_comments`: Number of comments (for posts)
- `upvote_ratio`: Upvote ratio (for posts)
- `flair`: Post or comment flair (if available)
- `permalink`: Direct Reddit link to the comment or post
- `url`: URL (if different from permalink)
- `subreddit`: Name of the subreddit
- `company`: The matched company keyword (`Apple`, `Tesla`, or `Microsoft`)
## Potential Use Cases
- Sentiment analysis
- Named Entity Recognition (NER)
- Text classification
- Experiments with Reddit and finance text data
## Data Collection
All comments were collected using [PRAW (Python Reddit API Wrapper)](https://praw.readthedocs.io/).
Full code and data processing pipeline can be found here:
➡️ [**emilpartow/financial-sentiment-pipeline**](https://github.com/emilpartow/financial-sentiment-pipeline)
## Notes
- All usernames and personal information are either removed or anonymized.
- **No manual or verbal content review was performed:** The dataset consists of comments as collected via the Reddit API. There may be offensive, biased, or otherwise inappropriate content present.
- Please respect Reddit’s API Terms of Use when working with this dataset.
## License
[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
---
**Questions or feedback?**
Feel free to open an issue or discussion in the linked GitHub repository! |