The Credibility Cryptocurrency Valuation: Statistical Learning Analysis for Influencer Tweets

Haemin Lee; Youngkee Kim; Hyunhee Cho; Soyi Jung; Joongheon Kim

doi:10.1109/ICOIN53446.2022.9687194

The Credibility Cryptocurrency Valuation: Statistical Learning Analysis for Influencer Tweets

Haemin Lee
, Youngkee Kim
, Hyunhee Cho
, Soyi Jung
, Joongheon Kim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Cryptocurrency has attracted significant attention. Considering the number of individuals investing in bitcoin, their motivations are comparatively less clear than traditional investment decisions. As of December 2020, the market has continuously increased in cryptocurrency. Especially, the spike of joke Dogecoin shows the weirdness of the modern meme economy with the support of Elon Musk, whom himself appointed as 'Dogefather'. In this paper, we analysis the impact of tweets by Elon musk and present some statistical analyze with event study.

Original language	English
Title of host publication	36th International Conference on Information Networking, ICOIN 2022
Publisher	IEEE Computer Society
Pages	58-61
Number of pages	4
ISBN (Electronic)	9781665413329
DOIs	https://doi.org/10.1109/ICOIN53446.2022.9687194
Publication status	Published - 2022
Event	36th International Conference on Information Networking, ICOIN 2022 - Virtual, Jeju Island, Korea, Republic of Duration: 2022 Jan 12 → 2022 Jan 15

Publication series

Name	International Conference on Information Networking
Volume	2022-January
ISSN (Print)	1976-7684

Conference

Conference	36th International Conference on Information Networking, ICOIN 2022
Country/Territory	Korea, Republic of
City	Virtual, Jeju Island
Period	22/1/12 → 22/1/15

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Cryptocurrency
Dogecoin
Twitter

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems

Access to Document

10.1109/ICOIN53446.2022.9687194

Cite this

Lee, H., Kim, Y., Cho, H., Jung, S., & Kim, J. (2022). The Credibility Cryptocurrency Valuation: Statistical Learning Analysis for Influencer Tweets. In 36th International Conference on Information Networking, ICOIN 2022 (pp. 58-61). (International Conference on Information Networking; Vol. 2022-January). IEEE Computer Society. https://doi.org/10.1109/ICOIN53446.2022.9687194

The Credibility Cryptocurrency Valuation: Statistical Learning Analysis for Influencer Tweets. / Lee, Haemin; Kim, Youngkee; Cho, Hyunhee et al.
36th International Conference on Information Networking, ICOIN 2022. IEEE Computer Society, 2022. p. 58-61 (International Conference on Information Networking; Vol. 2022-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, H, Kim, Y, Cho, H, Jung, S & Kim, J 2022, The Credibility Cryptocurrency Valuation: Statistical Learning Analysis for Influencer Tweets. in 36th International Conference on Information Networking, ICOIN 2022. International Conference on Information Networking, vol. 2022-January, IEEE Computer Society, pp. 58-61, 36th International Conference on Information Networking, ICOIN 2022, Virtual, Jeju Island, Korea, Republic of, 22/1/12. https://doi.org/10.1109/ICOIN53446.2022.9687194

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abstract = "Cryptocurrency has attracted significant attention. Considering the number of individuals investing in bitcoin, their motivations are comparatively less clear than traditional investment decisions. As of December 2020, the market has continuously increased in cryptocurrency. Especially, the spike of joke Dogecoin shows the weirdness of the modern meme economy with the support of Elon Musk, whom himself appointed as 'Dogefather'. In this paper, we analysis the impact of tweets by Elon musk and present some statistical analyze with event study.",

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The Credibility Cryptocurrency Valuation: Statistical Learning Analysis for Influencer Tweets

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this