Predicting the Popularity of Reddit Posts with AI

TL;DR

This paper develops and compares machine learning models to predict Reddit post popularity based on textual content, demonstrating neural networks as the most effective approach for forecasting upvotes.

Contribution

It introduces a neural network-based model for predicting Reddit post popularity and compares its performance with linear regression and random forest models.

Findings

Neural network outperformed other models in prediction accuracy.

Model trained on multiple subreddits showed robust performance.

Predicting post popularity can help anticipate social trends.

Abstract

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.