Speculative bubbles in cryptocurrency markets? An empirical investigation into Bitcoin's fundamental value on social media and its correlation with consumer behavior.

Abstract

This thesis thoroughly investigates how consumer opinions, on Twitter impact the value of Bitcoin, the currency. By utilizing sentiment analysis techniques through Natural Language Processing (NLP) the study aims to analyze tweets and their emotional context to comprehend how social media discussions influence consumer actions and market trends in the world of cryptocurrencies. The findings are relevant for economists, traders, investors, and policymakers as they offer insights that can help shape decisions and strategies concerning currencies. The research structure is meticulously outlined, explaining the underlying principles of the study design choices made, and methodologies utilized. Data collection involved gathering tweets related to Bitcoin along with corresponding market valuation information. The researcher emphasizes the need for maintaining study integrity, for replication purposes. The methodology section provides insights into analyzing consumer tweet's sentiment discussing both challenges faced and experimental setups employed. The analysis conducted shows how tweet sentiments and Bitcoin’s market value are related suggesting a connection, between these two factors. This research contributes to the understanding of sentiment analysis in markets by introducing aspect-based sentiment analysis to predict returns in cryptocurrencies. It also demonstrates how sentiment analysis can be practically applied in markets and improves accuracy by including sentiment features when forecasting Bitcoins returns. Moreover, the study emphasizes the long-term effects of tweets going beyond sentiment and trading activities to influence the development of new technologies and industries. These tweets guide interest, regulatory perspectives, and adoption trends.