This is a Python code that uses the Reddit API and several libraries to extract and analyze comments from the WallStreetBets subreddit. The code performs the following tasks:
Initializes the Reddit instance with user credentials
Sets program parameters, such as limit, upvotes, and picks
Initializes a sentiment analyzer
Extracts data from the subreddit by searching for posts with specific flairs and comments with a score greater than the defined upvotes threshold
Filters out comments that do not contain valid stock symbols
Converts the extracted data to a pandas DataFrame
Counts the frequency of each stock symbol and calculates the sentiment score for each symbol
Prints the top mentioned stock symbols and plots them as a word cloud
Plots the sentiment scores of the top picks as a horizontal bar chart.
The code uses the following libraries:
praw: Python Reddit API Wrapper, used to extract data from Reddit
pandas: data manipulation library, used to convert extracted data to a DataFrame
matplotlib: data visualization library, used to create the word cloud and bar chart
seaborn: data visualization library, used to create the horizontal bar chart
collections: Python built-in library, used to count the frequency of stock symbols
nltk: Natural Language Toolkit, used to perform sentiment analysis on comments
The data.py file is a module that contains a function named get_data() which the main program imports to access the Reddit API credentials. This helps keep sensitive information (such as API keys and passwords) separate from the main program, which is considered a good practice in software development.
Overall, the main program extracts comments from the subreddit, filters them based on specific criteria (e.g., minimum upvotes, post flairs), extracts stock symbols mentioned in the comments (e.g., $GME), performs sentiment analysis on the comments, and then generates two plots: a word cloud of the most frequently mentioned symbols and a bar chart of the sentiment scores for the top picks. This can help users understand the sentiment around specific stocks mentioned on the subreddit.
wordcloud: data visualization library, used to create the word cloud.