Discover how social media activity affects financial assets like Bitcoin and meme stocks. Visualize the link between online hype and market movement.
Understanding how the quality and volume of public opinion (Sentiment Score 0-100) dictates price ceilings and floors.
This density heatmap shows where the market spends most of its time. The brighter the color, the more data points exist in that range.
We broke down the data by individual asset to compare market maturity. Each coin is color-coded using the standard palette found in our other charts.
Established coins like DOGE have a wide, healthy spread across all sentiment levels. Newer "hype" coins cluster tightly, indicating they are extremely sensitive to momentary social trends.
Press Play to watch sentiment shifts in real-time.
Analyzing the relationship between posting volume (noise) and price action.
In this chart, time flows forward. The size of the bubble represents how many posts are being made about the coin. Each coin has a distinct color.
Watch closely: Does the bubble grow before the price shoots up? Or does the price shoot up, and then the bubble grows?
Use the sliders below to test our findings. Can you predict the price impact based on the variables?
Model Weighting: Sentiment (75%) vs Volume (25%)
A summary of our core findings, model assumptions, and a critique of the methodology.
Our analysis confirms a strong correlation between peak price action and sentiment scores above 90. Market tops are almost always accompanied by "Euphoric" social sentiment.
Established assets (like DOGE) exhibit wider sentiment distributions, meaning they can absorb negative sentiment without crashing. New coins lack this resilience.
Contrary to popular belief, high post volume often trails price action. The highest activity levels occur *after* the initial pump, indicating it is a reactive metric.
The Critique: First and foremeost, summaries and vidualizations are limited due to the lack of readily availale data through reddit and twitter API's. This has reduced our ability to provide more insightful findings regarding the posts themselves(i.e interactions, post quality and structere, etc). The project initially assumes that social media sentiment directly correlates with price movements in memecoins, but the data reveals that this relationship is often weak or inconsistent. In particular, general sentiment scores do not show strong linear correlations with price, which motivated the use of density-based visualizations to better capture dispersed patterns rather than simple trend lines. Because the data is historical, the visualizations are better suited for explaining past market behavior than making predictions. Overall, the results highlight the volatility and unpredictability of memecoins, reinforcing that sentiment is only one of many factors influencing these sensitive assets.
All social sentiment and post frequency data utilized in this project was sourced via the LunarCrush API.
Visit LunarCrush →Curated external analysis and academic studies.
An analysis from CoinGecko comparing the market behavior and investment characteristics of Bitcoin versus memecoins.
View Resource →This resource examines the mechanisms through which social media platforms fuel the rise and success of meme coins.
View Resource →Oliver Wyman's comprehensive analysis of cryptocurrency evolution, providing context for how digital assets have matured.
View Resource →A peer-reviewed academic paper investigating the quantitative relationship between social media activity and cryptocurrency market behavior.
View Resource →