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Predicting altcoin returns using social media

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  • Lars Steinert
  • Christian Herff

Abstract

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.

Suggested Citation

  • Lars Steinert & Christian Herff, 2018. "Predicting altcoin returns using social media," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-12, December.
  • Handle: RePEc:plo:pone00:0208119
    DOI: 10.1371/journal.pone.0208119
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    Cited by:

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    2. Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
    3. Bouteska, Ahmed & Hajek, Petr & Abedin, Mohammad Zoynul & Dong, Yizhe, 2023. "Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Fathin Faizah Said & Raja Solan Somasuntharam & Mohd Ridzwan Yaakub & Tamat Sarmidi, 2023. "Impact of Google searches and social media on digital assets’ volatility," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    5. Marten Risius & Christoph F. Breidbach & Mathieu Chanson & Ruben Krannichfeldt & Felix Wortmann, 2023. "On the performance of blockchain-based token offerings," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-19, December.
    6. Román Alejandro Mendoza Urdiales & Andrés García-Medina & José Antonio Nuñez Mora, 2021. "Measuring information flux between social media and stock prices with Transfer Entropy," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-19, September.
    7. Ana Fernández Vilas & Rebeca P. Díaz Redondo & Daniel Couto Cancela & Alejandro Torrado Pazos, 2021. "Interplay between Cryptocurrency Transactions and Online Financial Forums," Mathematics, MDPI, vol. 9(4), pages 1-22, February.
    8. Ana Fern'andez Vilas & Rebeca P. D'iaz Redondo & Daniel Couto Cancela & Alejandro Torrado Pazos, 2023. "Interplay between Cryptocurrency Transactions and Online Financial Forums," Papers 2401.10238, arXiv.org.

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