Social Media Engagement and Cryptocurrency Performance

TL;DR

This paper introduces a new social media engagement model to predict cryptocurrency performance, demonstrating that engagement levels and bot activity significantly influence future returns and can inform effective investment strategies.

Contribution

The paper presents a novel engagement measurement model that overcomes previous limitations and links social media engagement to cryptocurrency returns, highlighting the impact of bot activity.

Findings

Engagement coefficients correlate with future cryptocurrency returns.

High bot activity is associated with lower future returns.

Simple strategies based on engagement thresholds outperform random choices.

Abstract

We study the problem of predicting the future performance of cryptocurrencies using social media data. We propose a new model to measure the engagement of users with topics discussed on social media based on interactions with social media posts. This model overcomes the limitations of previous volume and sentiment based approaches. We use this model to estimate engagement coefficients for 48 cryptocurrencies created between 2019 and 2021 using data from Twitter from the first month of the cryptocurrencies' existence. We find that the future returns of the cryptocurrencies are dependent on the engagement coefficients. Cryptocurrencies whose engagement coefficients are too low or too high have lower returns. Low engagement coefficients signal a lack of interest, while high engagement coefficients signal artificial activity which is likely from automated accounts known as bots. We measure the amount of bot posts for the cryptocurrencies and find that generally, cryptocurrencies with more bot posts have lower future returns. While future returns are dependent on both the bot activity and engagement coefficient, the dependence is strongest for the engagement coefficient, especially for short-term returns. We show that simple investment strategies which select cryptocurrencies with engagement coefficients exceeding a fixed threshold perform well for holding times of a few months.