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 subs = [] sub-reddit to search postflairs = {} 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:" picksayz = int define # of picks for sentiment analysis 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.

⚠ No verified equity curve — no track-record source connected.

No score history is stored yet — only the current score is shown.

⚠ No live verification account connected — ask for proof before buying.

Alerts on changes: coming soon

Prop-firm compatibility not provided.

Data-completeness & trust index (not a profitability rating)