Using Social Media For Bitcoin Day Trading Behavior Prediction

Anna Paula Pawlicka Maule, Kristen Johnson


Abstract
This abstract presents preliminary work in the application of natural language processing techniques and social network modeling for the prediction of cryptocurrency trading and investment behavior. Specifically, we are building models to use language and social network behaviors to predict if the tweets of a 24-hour period can be used to buy or sell cryptocurrency to make a profit. In this paper we present our novel task and initial language modeling studies.
Anthology ID:
2020.winlp-1.37
Volume:
Proceedings of the The Fourth Widening Natural Language Processing Workshop
Month:
July
Year:
2020
Address:
Seattle, USA
Venues:
ACL | WS | WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
140–143
Language:
URL:
https://www.aclweb.org/anthology/2020.winlp-1.37
DOI:
10.18653/v1/2020.winlp-1.37
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