This program goes thru reddit, finds the most mentioned tickers and uses Vader SentimentIntensityAnalyzer to calculate the ticker compound value.
This program goes through reddit, finds the most mentioned tickers and uses Vader SentimentIntensityAnalyzer to calculate the ticker compound value.
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
pip install -r requirements.txt
python3 reddit-sentiment-analysis.py
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:
Bearish Neutral Bullish Total/Compound
GME 0.087 0.707 1.548 0.030
SPCE 0.119 0.645 1.618 0.027
PLTR 0.073 0.649 1.751 0.032
TSLA 0.088 0.650 1.543 0.049
MVIS 0.155 0.698 1.714 -0.020
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\
This project is licensed under the MIT License - see the LICENSE.md file for details.