Social media and bitcoin metrics: which words matter

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Social media and bitcoin metrics: which words matter

Burnie, A; Yilmaz, E; (2019) Social media and bitcoin metrics: which words matter. Royal Society Open Science , 6 (10) , Article 191068. 10.1098/rsos.191068. Green open access

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Abstract

We develop a new Data-Driven Phasic Word Identification (DDPWI) methodology to determine which words matter as the bitcoin pricing dynamic changes from one phase to another. With Google search volumes as a baseline, we find that Reddit submissions are both correlated with Google and have a comparable relationship with a variety of bitcoin metrics, using Spearman’s rho. Reddit provides complete access to the text of submissions. Rather than associating sentiment with market activity, we describe the DDPWI method for finding specific ‘price dynamic’ words associated with changes in the bitcoin pricing pattern through 2017 and 2018. We assess the significance of these changes using Wilcoxon Rank-Sum Tests with Bonferroni corrections. These price dynamic words are used to pull out associated words in the submissions thereby providing the context to their use. For example, the price dynamic word ‘ban’, which became significantly higher in frequency as prices fell, occurred in the context of both government regulation and internet companies banning cryptocurrency adverts. This approach could be used more generally to look at social media and discussion forums at a granular level identifying specific words that impact the metric under investigation rather than overall sentiment.

Type:	Article
Title:	Social media and bitcoin metrics: which words matter
Open access status:	An open access version is available from UCL Discovery
DOI:	10.1098/rsos.191068
Publisher version:	https://doi.org/10.1098/rsos.191068
Language:	English
Additional information:	© 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).
Keywords:	Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, bitcoin, non-parametric statistics, social media, Reddit, text analysis, sentiment
UCL classification:	UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI:	https://discovery.ucl.ac.uk/id/eprint/10113185