  Social media creates crucial mass changes, as popular posts and opinions cast
a significant influence on users' decisions and thought processes. For example,
the recent Reddit uprising inspired by r/wallstreetbets which had remarkable
economic impact was started with a series of posts on the thread. The
prediction of posts that may have a notable impact will allow for the
preparation of possible following trends. This study aims to develop a machine
learning model capable of accurately predicting the popularity of a Reddit
post. Specifically, the model is predicting the number of upvotes a post will
receive based on its textual content. I experimented with three different
models: a baseline linear regression model, a random forest regression model,
and a neural network. I collected Reddit post data from an online data set and
analyzed the model's performance when trained on a single subreddit and a
collection of subreddits. The results showed that the neural network model
performed the best when the loss of the models were compared. With the use of a
machine learning model to predict social trends through the reaction users have
to post, a better picture of the near future can be envisioned.
