reddit-sentiment-analysis - GitLite

KO | EN

gitlite — search

#react #ai #typescript #llm #go #golang #android #rust #deep-learning #docker #cli #security #ios #openai

reddit-sentiment-analysis

(★ 286)

license

last commit

Open GitHub ↗

This program goes thru reddit, finds the most mentioned tickers and uses Vader SentimentIntensityAnalyzer to calculate the ticker compound value.

File Explorer

Download Latest Version (.zip)

- data.cpython-37.pyc
data.py
LICENSE.md
list of subreddits.csv
mentioned.png
README.md
reddit-sentiment-analysis.py
requirements.txt
sentiment.png

# Installation Guide

1. Get the code

git clone https://github.com/asad70/reddit-sentiment-analysis

Downloads the entire project code from GitHub to your computer.

cd reddit-sentiment-analysis

Moves into the project folder you just downloaded.

2. Python

Easy Recommended

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install -r requirements.txt

Installs the Python libraries listed in requirements.txt (or similar).

✅ If it runs without errors and prints output in the terminal, it worked.

Pulled directly from this repo's README.

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# reddit-sentiment-analysis
This program goes through reddit, finds the most mentioned tickers and uses Vader SentimentIntensityAnalyzer to calculate the ticker compound value.

## Program Parameters
<pre>
subs = []           sub-reddit to search
post_flairs = {}    posts flairs to search || None flair is automatically considered
goodAuth = {}       authors whom comments are allowed more than once
uniqueCmt = True    allow one comment per author per symbol
ignoreAuthP = {}    authors to ignore for posts
ignoreAuthC = {}    authors to ignore for comment 
upvoteRatio = float upvote ratio for post to be considered, 0.70 = 70%
ups = int           define # of upvotes, post is considered if upvotes exceed this #
limit = int         define the limit, comments 'replace more' limit
upvotes = int       define # of upvotes, comment is considered if upvotes exceed this #
picks = int         define # of picks here, prints as "Top ## picks are:"
picks_ayz = int     define # of picks for sentiment analysis
</pre>

# How to run:
    
    pip install -r requirements.txt
    python3 reddit-sentiment-analysis.py
    
    
## Sample Output
It took 1574.61 seconds to analyze 14236 comments in 8 posts in 1 subreddits.

Posts analyzed saved in titles

10 most mentioned picks:\
GME: 764\
SPCE: 183\
PLTR: 89\
TSLA: 71\
MVIS: 42\
NVDA: 34\
AMD: 30\
F: 29\
TLRY: 29\
AAPL: 26

Sentiment analysis of top 5 picks:\
     &nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp;Bearish &nbsp;Neutral &nbsp;Bullish&nbsp; Total/Compound\
GME   &nbsp; 0.087  &nbsp; 0.707  &nbsp;&nbsp; 1.548    &nbsp;&nbsp;&nbsp;      0.030\
SPCE  &nbsp; 0.119  &nbsp; 0.645  &nbsp;&nbsp; 1.618    &nbsp;&nbsp;&nbsp;      0.027\
PLTR  &nbsp; 0.073  &nbsp; 0.649  &nbsp;&nbsp; 1.751    &nbsp;&nbsp;&nbsp;      0.032\
TSLA  &nbsp; 0.088  &nbsp; 0.650  &nbsp;&nbsp; 1.543    &nbsp;&nbsp;&nbsp;      0.049\
MVIS  &nbsp; 0.155  &nbsp; 0.698  &nbsp;&nbsp; 1.714    &nbsp;&nbsp;&nbsp;     -0.020
![](https://raw.githubusercontent.com/asad70/reddit-sentiment-analysis/master/mentioned.png)
![](https://raw.githubusercontent.com/asad70/reddit-sentiment-analysis/master/sentiment.png)

## Data:
Includes US stocks with market cap > 100 Million, and price above $3. It doesn't include penny stocks.\
You can download data from here:\
Source (US stocks):  https://www.nasdaq.com/market-activity/stocks/screener?exchange=nasdaq&letter=0&render=download\

## License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.