4.4 Q9: Impact of High-profile Events on Community and Market Attitudes
[🔗Github Link]
4.4.1 The impact of Elon Musk’s tweet on dogecoin-related posts
Question 6 explores the influence of a tweet by Elon Musk, where he posted a picture of Shiba wearing a Twitter T-shirt, on the price of Dogecoin. We observed a significant increase in price following this tweet. This analysis extends to examine whether similar patterns occur in the volume and nature of discussions about Dogecoin on Reddit. We apply machine learning-based causal inference methods to determine if there is a causal relationship between such high-profile events and the behavior within the Dogecoin community on Reddit.
We focus on two main indicators of discussion behavior: sentiment and mentions of buying signals, both closely linked to price fluctuations. This approach allows us to discern the behavioral shifts in the community in response to significant events. 
We focus on two main indicators of discussion behavior: sentiment and mentions of buying signals, both closely linked to price fluctuations. This approach allows us to discern the behavioral shifts in the community in response to significant events.
Synapse ML for Causal Inference
For the causal inference, we are using Synapse ML in Apache Spark . SynapseML (previously known as MMLSpark), is an open-source library designed to streamline the development of scalable machine learning pipelines, to analyze causal effects and heterogeneous responses in observational data.
4.4.2 Causal Inference with the DoubleML estimator
We define a period of 14 days before and after the tweet on November 1, 2022, to analyze changes in community behavior.
Treatment: Before or After Tweet Post Outcome: Average Sentiment/ Buy Signal Proportion
| Treatment Effect | Confidence Interval | If Casual | |
|---|---|---|---|
| Sentiment | 0.06 | (0.0376, 0.0824) | Yes |
| Buy Signal | 0.324 | (0.1141, 0.4499) | Yes |
The analysis reveals a moderate treatment effect on sentiment (0.06), indicating that while Musk’s tweet positively influenced the sentiment within the Dogecoin community, the impact was modest yet statistically significant. This suggests that influential tweets may sway public sentiment but typically do not cause drastic changes unless paired with significant market developments.
Conversely, the effect on buy signals was substantially stronger (0.324), pointing to a more marked behavioral response in terms of investment and trading activities. This larger effect size highlights the power of prominent social media figures to initiate substantial market actions, likely fueled by perceived endorsements or speculative optimism following the tweet.
Overall, the evidence supports a causal relationship between Musk’s tweet and changes in both sentiment and buying behavior within the Dogecoin community on Reddit. These findings underscore the broader impact of social media on cryptocurrency markets, where a single influential post can significantly alter market dynamics and investor behavior.