Cargando…

Social media engagement and cryptocurrency performance

Cryptocurrencies are highly speculative assets with large price volatility. If one could forecast their behavior, this would make them more attractive to investors. In this work we study the problem of predicting the future performance of cryptocurrencies using social media data. We propose a new mo...

Descripción completa

Detalles Bibliográficos
Autores principales: Qureshi, Khizar, Zaman, Tauhid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10174546/
https://www.ncbi.nlm.nih.gov/pubmed/37167281
http://dx.doi.org/10.1371/journal.pone.0284501
_version_ 1785040055638687744
author Qureshi, Khizar
Zaman, Tauhid
author_facet Qureshi, Khizar
Zaman, Tauhid
author_sort Qureshi, Khizar
collection PubMed
description Cryptocurrencies are highly speculative assets with large price volatility. If one could forecast their behavior, this would make them more attractive to investors. In this work we study the problem of predicting the future performance of cryptocurrencies using social media data. We propose a new model to measure the engagement of users with topics discussed on social media based on interactions with social media posts. This model overcomes the limitations of previous volume and sentiment based approaches. We use this model to estimate engagement coefficients for 48 cryptocurrencies created between 2019 and 2021 using data from Twitter from the first month of the cryptocurrencies’ existence. We find that the future returns of the cryptocurrencies are dependent on the engagement coefficients. Cryptocurrencies whose engagement coefficients have extreme values have lower returns. Low engagement coefficients signal a lack of interest, while high engagement coefficients signal artificial activity which is likely from automated accounts known as bots. We measure the amount of bot posts for the cryptocurrencies and find that generally, cryptocurrencies with more bot posts have lower future returns. While future returns are dependent on both the bot activity and engagement coefficient, the dependence is strongest for the engagement coefficient, especially for short-term returns. We show that simple investment strategies which select cryptocurrencies with engagement coefficients exceeding a fixed threshold perform well for holding times of a few months.
format Online
Article
Text
id pubmed-10174546
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-101745462023-05-12 Social media engagement and cryptocurrency performance Qureshi, Khizar Zaman, Tauhid PLoS One Research Article Cryptocurrencies are highly speculative assets with large price volatility. If one could forecast their behavior, this would make them more attractive to investors. In this work we study the problem of predicting the future performance of cryptocurrencies using social media data. We propose a new model to measure the engagement of users with topics discussed on social media based on interactions with social media posts. This model overcomes the limitations of previous volume and sentiment based approaches. We use this model to estimate engagement coefficients for 48 cryptocurrencies created between 2019 and 2021 using data from Twitter from the first month of the cryptocurrencies’ existence. We find that the future returns of the cryptocurrencies are dependent on the engagement coefficients. Cryptocurrencies whose engagement coefficients have extreme values have lower returns. Low engagement coefficients signal a lack of interest, while high engagement coefficients signal artificial activity which is likely from automated accounts known as bots. We measure the amount of bot posts for the cryptocurrencies and find that generally, cryptocurrencies with more bot posts have lower future returns. While future returns are dependent on both the bot activity and engagement coefficient, the dependence is strongest for the engagement coefficient, especially for short-term returns. We show that simple investment strategies which select cryptocurrencies with engagement coefficients exceeding a fixed threshold perform well for holding times of a few months. Public Library of Science 2023-05-11 /pmc/articles/PMC10174546/ /pubmed/37167281 http://dx.doi.org/10.1371/journal.pone.0284501 Text en © 2023 Qureshi, Zaman https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Qureshi, Khizar
Zaman, Tauhid
Social media engagement and cryptocurrency performance
title Social media engagement and cryptocurrency performance
title_full Social media engagement and cryptocurrency performance
title_fullStr Social media engagement and cryptocurrency performance
title_full_unstemmed Social media engagement and cryptocurrency performance
title_short Social media engagement and cryptocurrency performance
title_sort social media engagement and cryptocurrency performance
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10174546/
https://www.ncbi.nlm.nih.gov/pubmed/37167281
http://dx.doi.org/10.1371/journal.pone.0284501
work_keys_str_mv AT qureshikhizar socialmediaengagementandcryptocurrencyperformance
AT zamantauhid socialmediaengagementandcryptocurrencyperformance