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Predicting altcoin returns using social media
Cryptocurrencies have recently received large media interest. Especially the great fluctuations in price have attracted such attention. Behavioral sciences and related scientific literature provide evidence that there is a close relationship between social media and price fluctuations of cryptocurre...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279012/ https://www.ncbi.nlm.nih.gov/pubmed/30513110 http://dx.doi.org/10.1371/journal.pone.0208119 |
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author | Steinert, Lars Herff, Christian |
author_facet | Steinert, Lars Herff, Christian |
author_sort | Steinert, Lars |
collection | PubMed |
description | Cryptocurrencies have recently received large media interest. Especially the great fluctuations in price have attracted such attention. Behavioral sciences and related scientific literature provide evidence that there is a close relationship between social media and price fluctuations of cryptocurrencies. This particularly applies to smaller currencies, which can be substantially influenced by references on Twitter. Although these so-called “altcoins” often have smaller trading volumes they sometimes attract large attention on social media. Here, we show that fluctuations in altcoins can be predicted from social media. In order to do this, we collected a dataset containing prices and the social media activity of 181 altcoins in the form of 426,520 tweets over a timeframe of 71 days. The containing public mood was then estimated using sentiment analysis. To predict altcoin returns, we carried out linear regression analyses based on 45 days of data. We showed that short-term returns can be predicted from activity and sentiments on Twitter. |
format | Online Article Text |
id | pubmed-6279012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62790122018-12-20 Predicting altcoin returns using social media Steinert, Lars Herff, Christian PLoS One Research Article Cryptocurrencies have recently received large media interest. Especially the great fluctuations in price have attracted such attention. Behavioral sciences and related scientific literature provide evidence that there is a close relationship between social media and price fluctuations of cryptocurrencies. This particularly applies to smaller currencies, which can be substantially influenced by references on Twitter. Although these so-called “altcoins” often have smaller trading volumes they sometimes attract large attention on social media. Here, we show that fluctuations in altcoins can be predicted from social media. In order to do this, we collected a dataset containing prices and the social media activity of 181 altcoins in the form of 426,520 tweets over a timeframe of 71 days. The containing public mood was then estimated using sentiment analysis. To predict altcoin returns, we carried out linear regression analyses based on 45 days of data. We showed that short-term returns can be predicted from activity and sentiments on Twitter. Public Library of Science 2018-12-04 /pmc/articles/PMC6279012/ /pubmed/30513110 http://dx.doi.org/10.1371/journal.pone.0208119 Text en © 2018 Steinert, Herff http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 Steinert, Lars Herff, Christian Predicting altcoin returns using social media |
title | Predicting altcoin returns using social media |
title_full | Predicting altcoin returns using social media |
title_fullStr | Predicting altcoin returns using social media |
title_full_unstemmed | Predicting altcoin returns using social media |
title_short | Predicting altcoin returns using social media |
title_sort | predicting altcoin returns using social media |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279012/ https://www.ncbi.nlm.nih.gov/pubmed/30513110 http://dx.doi.org/10.1371/journal.pone.0208119 |
work_keys_str_mv | AT steinertlars predictingaltcoinreturnsusingsocialmedia AT herffchristian predictingaltcoinreturnsusingsocialmedia |