- Connect to gsheets for later: https://docs.google.com/spreadsheets/d/1rX4mniePZLIUCIFd7H2EdMioR_ip3LhtAjxJ2VclvXg/edit?usp=sharing
- Connect to Reddit
- Load top 1000 /r/bitcoin hot posts
- Take the raw text, split it into an array on newline chars, filter out empty strings
- Create an array of judged sentiments from the Natural Language Toolkkit’s Vader function for each string in array from step 4
- For each of the sentiments from step 5, grab the compound (overall) sentiment rating (which is based on values attributed to keywords and etc., wort a search on your favorite engine) and check if it’s above or below a threshold value, then make them lowercase and replace ‘bitcoin’ with ‘our coin’ and ‘btc’ with ‘our ticker’ and ensure the string doesn’t start with a shady substring then append the results to our positives && negatives arrays
- Loop 10 times
- For a range of maximum 6 strings, for first positive strings then negative strings take a random choice (so long as it’s not already taken) and add it to a series of final sets of superpowerful strings
- Print a bunch of useful information to terminal in the process of steps 7–8
- Finally add a row to Positives and Negatives gsheet for each of the 10 superstrings
In an ideal world, people would use a variation of this script to load and replace keyword strings from many crypto-based subreddits, then push the final superstrings through a (good) word spinner, then post the resulting strings to create FOMO or FUD for a given perp.
Opensource Reddit Sentiment Analysis and Sentence Randomizer was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.