---
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 Posts Sample Dataset (Apple/Tesla/Microsoft)
size_categories:
- 10K<n<100K
---
# Reddit Finance Posts Dataset (Apple, Tesla, Microsoft)

This dataset contains 12046 Reddit Posts collected from 20 finance-related subreddits via the Reddit API using the keywords **Apple**, **Tesla**, and **Microsoft**.
The included subreddits are:

```
stocks, wallstreetbets, investing, StockMarket, options, RobinHood,
pennystocks, SecurityAnalysis, personalfinance, Dividends, CryptoCurrency,
CryptoMarkets, ETFs, FinancialIndependence, ValueInvesting, quant,
algotrading, forex, economy, Superstonk, spacs, financialplanning
```

## 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 post ID  
- `title`: Title of the post  
- `text`: Body text of the post (if available)
- `created_utc`: Timestamp in UTC  
- `created_datetime`: Datetime (ISO format)  
- `author`: Reddit username  
- `score`: Reddit score (upvotes minus downvotes)  
- `num_comments`: Number of comments (for posts)  
- `upvote_ratio`: Upvote ratio (for posts)  
- `flair`: Post  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 posts 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

- **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!