  This study investigates the relationship between narratives conveyed through
microblogging platforms, namely Twitter, and the value of crypto assets. Our
study provides a unique technique to build narratives about cryptocurrency by
combining topic modelling of short texts with sentiment analysis. First, we
used an unsupervised machine learning algorithm to discover the latent topics
within the massive and noisy textual data from Twitter, and then we revealed
4-5 cryptocurrency-related narratives, including financial investment,
technological advancement related to crypto, financial and political
regulations, crypto assets, and media coverage. In a number of situations, we
noticed a strong link between our narratives and crypto prices. Our work
connects the most recent innovation in economics, Narrative Economics, to a new
area of study that combines topic modelling and sentiment analysis to relate
consumer behaviour to narratives.
