osgoodbl/reddit-analysis

A Natural Language Processing of Reddit Posts

Project Summary

Initial Project Scope:

Determine if it is possible to predict if a Reddit post can garner above the median number of comments. The median was calculated from the total number of comments scraped on posts from May 29th to June 1st.

Secondary Project Scope:

Build a model to predict a posts likelihood to gain a score over 15,000. This would make the post 'Hot' by Reddit standards.

Project Description

Creating a dataset derived from live web data: Reddit.com Utilizing Machine learning along with the Python requests library, multiple models were built and tested to the scopes. A Logistic Regression Model showed that a post could be inferred to meet the target amount of comments with 73% accuracy. This fulfilled the initial scope.

Using the same data, a Logistic Regression model was then used again to model a post score greater than the target. This model was able to reach 95.4% accuracy of predicting a posts score based on the subreddit and title words. This fulfilled the secondary scope.

Project Resources:

Reddit Hot

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