AIS - a Metric for assessing the Impact of an Influencer's Twitter Activity on the Price of a Cryptocurrency

Kevin Miller; Kristof Böhmer

doi:10.1007/978-3-031-46846-9_3

AIS - a Metric for assessing the Impact of an Influencer's Twitter Activity on the Price of a Cryptocurrency

Kevin Miller, Kristof Böhmer

Research Group Software Architecture

Publications: Contribution to book › Contribution to proceedings › Peer Reviewed

Abstract

Individual users on social media platforms like Twitter can significantly volatile assets, including cryptocurrencies. However, current research has overlooked this aspect, focusing on sentiment analysis that includes all posts from all users. Making it challenging to detect trends caused by individuals. To address this gap, we introduce the Asset Influence Score (AIS), a percentage-based metric that assesses the likelihood of a newly issued tweet aligning with periods of heightened trading activity. By analyzing price data and tweets concurrently, we identify correlations that enable to predict the likelihood of specific users’ tweets co-occurring with increased trading activity. Evaluating the AIS using a publicly available prototype and Twitter data from 2020 to 2023, we find that using the AIS as a buy signal outperforms buy-and-hold and technical trading strategies while maintaining high liquidity. Demonstrating the applicability of AIS in improving trading decisions and identifying key individuals on social media platforms.

Original language	English
Title of host publication	Cooperative Information Systems
Subtitle of host publication	29th International Conference, CoopIS 2023, Groningen, The Netherlands, October 30–November 3, 2023, Proceedings
Editors	Mohamed Sellami, Walid Gaaloul, Maria-Esther Vidal, Boudewijn van Dongen, Hervé Panetto
Place of Publication	Cham
Publisher	Springer
Pages	41-58
Number of pages	18
ISBN (Electronic)	978-3-031-46846-9
ISBN (Print)	978-3-031-46845-2
DOIs	https://doi.org/10.1007/978-3-031-46846-9_3
Publication status	Published - 2024
Event	29th International Conference on Cooperative Information Systems - Groningen, Netherlands Duration: 30 Oct 2023 → 3 Nov 2023 https://coopisconference.org/

Conference

Conference	29th International Conference on Cooperative Information Systems
Abbreviated title	CoopIS 2023
Country/Territory	Netherlands
City	Groningen
Period	30/10/23 → 3/11/23
Internet address	https://coopisconference.org/

Austrian Fields of Science 2012

102022 Software development

Keywords

Cryptocurrency
Prediction
Social Media Analysis
Trading Indicator
Twitter

Access to Document

10.1007/978-3-031-46846-9_3

http://eprints.cs.univie.ac.at/7816/

Cite this

Miller, K., & Böhmer, K. (2024). AIS - a Metric for assessing the Impact of an Influencer's Twitter Activity on the Price of a Cryptocurrency. In M. Sellami, W. Gaaloul, M.-E. Vidal, B. van Dongen, & H. Panetto (Eds.), Cooperative Information Systems: 29th International Conference, CoopIS 2023, Groningen, The Netherlands, October 30–November 3, 2023, Proceedings (pp. 41-58). Springer. https://doi.org/10.1007/978-3-031-46846-9_3

Miller, Kevin ; Böhmer, Kristof. / AIS - a Metric for assessing the Impact of an Influencer's Twitter Activity on the Price of a Cryptocurrency. Cooperative Information Systems: 29th International Conference, CoopIS 2023, Groningen, The Netherlands, October 30–November 3, 2023, Proceedings. editor / Mohamed Sellami ; Walid Gaaloul ; Maria-Esther Vidal ; Boudewijn van Dongen ; Hervé Panetto. Cham : Springer, 2024. pp. 41-58

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abstract = "Individual users on social media platforms like Twitter can significantly volatile assets, including cryptocurrencies. However, current research has overlooked this aspect, focusing on sentiment analysis that includes all posts from all users. Making it challenging to detect trends caused by individuals. To address this gap, we introduce the Asset Influence Score (AIS), a percentage-based metric that assesses the likelihood of a newly issued tweet aligning with periods of heightened trading activity. By analyzing price data and tweets concurrently, we identify correlations that enable to predict the likelihood of specific users{\textquoteright} tweets co-occurring with increased trading activity. Evaluating the AIS using a publicly available prototype and Twitter data from 2020 to 2023, we find that using the AIS as a buy signal outperforms buy-and-hold and technical trading strategies while maintaining high liquidity. Demonstrating the applicability of AIS in improving trading decisions and identifying key individuals on social media platforms.",

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Miller, K & Böhmer, K 2024, AIS - a Metric for assessing the Impact of an Influencer's Twitter Activity on the Price of a Cryptocurrency. in M Sellami, W Gaaloul, M-E Vidal, B van Dongen & H Panetto (eds), Cooperative Information Systems: 29th International Conference, CoopIS 2023, Groningen, The Netherlands, October 30–November 3, 2023, Proceedings. Springer, Cham, pp. 41-58, 29th International Conference on Cooperative Information Systems, Groningen, Netherlands, 30/10/23. https://doi.org/10.1007/978-3-031-46846-9_3

AIS - a Metric for assessing the Impact of an Influencer's Twitter Activity on the Price of a Cryptocurrency. / Miller, Kevin; Böhmer, Kristof.
Cooperative Information Systems: 29th International Conference, CoopIS 2023, Groningen, The Netherlands, October 30–November 3, 2023, Proceedings. ed. / Mohamed Sellami; Walid Gaaloul; Maria-Esther Vidal; Boudewijn van Dongen; Hervé Panetto. Cham: Springer, 2024. p. 41-58.

Publications: Contribution to book › Contribution to proceedings › Peer Reviewed

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AU - Miller, Kevin

AU - Böhmer, Kristof

PY - 2024

Y1 - 2024

N2 - Individual users on social media platforms like Twitter can significantly volatile assets, including cryptocurrencies. However, current research has overlooked this aspect, focusing on sentiment analysis that includes all posts from all users. Making it challenging to detect trends caused by individuals. To address this gap, we introduce the Asset Influence Score (AIS), a percentage-based metric that assesses the likelihood of a newly issued tweet aligning with periods of heightened trading activity. By analyzing price data and tweets concurrently, we identify correlations that enable to predict the likelihood of specific users’ tweets co-occurring with increased trading activity. Evaluating the AIS using a publicly available prototype and Twitter data from 2020 to 2023, we find that using the AIS as a buy signal outperforms buy-and-hold and technical trading strategies while maintaining high liquidity. Demonstrating the applicability of AIS in improving trading decisions and identifying key individuals on social media platforms.

AB - Individual users on social media platforms like Twitter can significantly volatile assets, including cryptocurrencies. However, current research has overlooked this aspect, focusing on sentiment analysis that includes all posts from all users. Making it challenging to detect trends caused by individuals. To address this gap, we introduce the Asset Influence Score (AIS), a percentage-based metric that assesses the likelihood of a newly issued tweet aligning with periods of heightened trading activity. By analyzing price data and tweets concurrently, we identify correlations that enable to predict the likelihood of specific users’ tweets co-occurring with increased trading activity. Evaluating the AIS using a publicly available prototype and Twitter data from 2020 to 2023, we find that using the AIS as a buy signal outperforms buy-and-hold and technical trading strategies while maintaining high liquidity. Demonstrating the applicability of AIS in improving trading decisions and identifying key individuals on social media platforms.

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KW - Prediction

KW - Social Media Analysis

KW - Trading Indicator

KW - Twitter

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A2 - Gaaloul, Walid

A2 - Vidal, Maria-Esther

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Miller K, Böhmer K. AIS - a Metric for assessing the Impact of an Influencer's Twitter Activity on the Price of a Cryptocurrency. In Sellami M, Gaaloul W, Vidal ME, van Dongen B, Panetto H, editors, Cooperative Information Systems: 29th International Conference, CoopIS 2023, Groningen, The Netherlands, October 30–November 3, 2023, Proceedings. Cham: Springer. 2024. p. 41-58 Epub 2023 Oct 25. doi: 10.1007/978-3-031-46846-9_3

AIS - a Metric for assessing the Impact of an Influencer's Twitter Activity on the Price of a Cryptocurrency

Abstract

Conference

Austrian Fields of Science 2012

Keywords

Access to Document

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