Noise trader impact: Bitcoin market evidence from Telegram and X

As interest in Bitcoin as an investment asset continues to rise, this study investigates how social media influencers’ statements impact Bitcoin price through sentiment and time series analysis. The research employs data from Telegram and compares it with X (formerly Twitter) to examine their effects on Bitcoin price and trading volume fluctuations using a Vector Autoregressive model. In the short-term, focusing on the five days following a shock, negative sentiment affects future price changes negatively for the first two days, while positive sentiment has a positive impact; the direction of the shock reverses after the third day. These findings align with the noise trader theory, supporting the interaction between noise traders and rational traders in the Bitcoin market. Further analysis using the NRC Word-Emotion Association Lexicon (EmoLex) to measure the occurrence of eight basic emotion words (joy, trust, fear, surprise, sadness, disgust, anger, anticipation) revealed that messages from Bitcoin channels on Telegram often convey strong trust and anticipation, suggesting a potential stimulation of noise traders’ investment activities. In contrast, posts by Bitcoin influencers on X frequently employ emotionally charged words, likely contributing to the spread and amplification of sentiment among noise traders. These results suggest that messages from social media influencers function as a valuable information source for noise traders, potentially impacting their short-term behavior. This study contributes to understanding the dynamics of the Bitcoin market and offers insights into the intersection of social media and Bitcoin market movements, providing valuable information for researchers and investors.