THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS

Lyu Jia-Ying

doi:10.17261/Pressacademia.2025.2008

THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS

Abstract

Purpose- This study investigates the manifestation of the Abilene Paradox within the context of collective irrational behavior in cryptocurrency markets, utilizing social media data for sentiment analysis. The Abilene Paradox describes a phenomenon where a group collectively decides on a course of action that is contrary to the preferences of most or all individuals, as each mistakenly believes it aligns with the desires of others. In the highly community-driven cryptocurrency market, this paradox can exacerbate herd behavior and the Fear of Missing Out (FOMO), leading to significant market volatility. Methodology- Through sentiment analysis of discussions on social media platforms (e.g., Twitter, Reddit) concerning specific cryptocurrencies (e.g., Meme Coins), this research explores how community sentiment influences market behavior and price movements. Findings- The study considers the impact of community variables (e.g., community size, opinion leader influence), sentiment variables (e.g., positive/negative sentiment indices, sentiment polarization), and market variables (e.g., trading volume, price volatility) on collective irrational behavior. Conclusion- It aims to establish a generalized model explaining the relationship between social media sentiment and market behavior. The findings will contribute to understanding the behavioral economics characteristics of cryptocurrency markets and offer new perspectives for investors and regulators.

Keywords

References

Anaza, N. A., Upadhyaya, B., Bennett, D. H. S., & Ruvalcaba, C. (2024). Is it FOMO or is it ME? The influence of personality traits on cryptocurrency consumption. Psychology & Marketing, 41(1), 184–202. https://doi.org/10.1002/mar.21919
Antweiler, W., & Frank, M. Z. (2004). Is all that talk just noise? The information content of Internet stock message boards. The Journal of Finance, 59(3), 1259–1294. https://doi.org/10.1111/j.1540-6261.2004.00662.x
Banerjee, A. V. (1992). A simple model of herd behavior. The Quarterly Journal of Economics, 107(3), 797–817. https://doi.org/10.2307/2118364
Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261–292. https://doi.org/10.1162/003355301556400
Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177–189. https://doi.org/10.1016/j.intfin.2017.12.004
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.
Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1–8. https://doi.org/10.1016/j.jocs.2010.12.007
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1

Corbet, S., Lucey, B., & Yarovaya, L. (2018). Datestamping the Bitcoin and Ethereum bubbles. Finance Research Letters, 26, 81–88. https://doi.org/10.1016/j.frl.2017.12.006
Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. The Journal of Finance, 66(5), 1461–1499. https://doi.org/10.1111/j.1540- 6261.2011.01679.x
Esser, J. K., & Lindoerfer, J. S. (1989). Groupthink and the space shuttle Challenger accident: Toward a quantitative case analysis. Journal of Behavioral Decision Making, 2(3), 167–177. https://doi.org/10.1002/bdm.3960020304
Financial Conduct Authority. (2024). FG24/1: Finalised guidance on financial promotions on social media. https://www.fca.org.uk/
Financial Industry Regulatory Authority. (2024). 2024 FINRA annual regulatory oversight report. https://www.finra.org/
Gandal, N., Hamrick, J. T., Moore, T., & Oberman, T. (2018). Price manipulation in the Bitcoin ecosystem. Journal of Monetary Economics, 95, 86–96. https://doi.org/10.1016/j.jmoneco.2017.12.004
Gong, Y., Tang, X., & Chang, E.-C. (2023). Group norms and policy norms trigger different autonomous motivations for Chinese investors in cryptocurrency investment. Humanities and Social Sciences Communications, 10, 521. https://doi.org/10.1057/s41599-023-01870-0
Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438. https://doi.org/10.2307/1912791
Gurdgiev, C., & O’Loughlin, D. (2020). Herding and anchoring in cryptocurrency markets: Investor reaction to fear and greed. Journal of Behavioral and Experimental Finance, 25, 100358. https://doi.org/10.1016/j.jbef.2019.100358
Harvey, J. B. (1974). The Abilene paradox: The management of agreement. Organizational Dynamics, 3(1), 63–80. https://doi.org/10.1016/0090-2616(74)90005-9
Harvey, J. B. (1988). The Abilene paradox and other meditations on management. Lexington Books.
Heuer, R. J., Jr., & Pherson, R. H. (2010). Structured analytic techniques for intelligence analysis. CQ Press.,
Hirschheim, R., & Newman, M. (1991). Symbolism and information systems development: Myth, metaphor and magic. Information Systems Research, 2(1), 29–62. https://doi.org/10.1287/isre.2.1.29
Hutto, C. J., & Gilbert, E. (2014). VADER: A parsimonious rule-based model for sentiment analysis of social media text. In Proceedings of the 8th International AAAI Conference on Weblogs and Social Media (pp. 216–225). https://doi.org/10.1609/icwsm.v8i1.14550
International Organization of Securities Commissions. (2023). Retail Market Conduct Task Force: Final report (FR05/23). https://www.iosco.org/
International Organization of Securities Commissions. (2024). Finfluencers (CR/08/2024). https://www.iosco.org/
Janis, I. L. (1972). Victims of groupthink: A psychological study of foreign-policy decisions and fiascoes. Houghton Mifflin.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185
Kim, J., Lee, D., & Park, S. (2025). Opinion leaders, viral memes, and collective mispricing in cryptocurrency markets. Finance Research Letters, 65, 105293. https://doi.org/10.1016/j.frl.2024.105293
Kraaijeveld, O., & De Smedt, J. (2020). The predictive power of public Twitter sentiment for forecasting cryptocurrency prices. Journal of International Financial Markets, Institutions and Money, 65, 101188. https://doi.org/10.1016/j.intfin.2020.101188
Kuran, T. (1995). Private truths, public lies: The social consequences of preference falsification. Harvard University Press.
Li, Y., Liu, Z., & Shi, Y. (2024). False consensus and online financial decision-making: Evidence from crypto communities. Computers in Human Behavior, 152, 107325. https://doi.org/10.1016/j.chb.2023.107325
Long, H.-W., Wong, N.-M., & Cai, W. (2025). Bridging culture and finance: A multimodal analysis of memecoins in the Web3 ecosystem. In Companion Proceedings of the ACM Web Conference 2025 (pp. 1158–1161). https://doi.org/10.1145/3701716.3715561
Long, S. C., Xie, Y., Zhou, Z., Lucey, B. M., & Urquhart, A. (2025). From whales to waves: Social media sentiment, volatility, and whales in cryptocurrency markets. The British Accounting Review, 57(1), 101266. https://doi.org/10.1016/j.bar.2024.101266
Merton, R. C. (1973). An intertemporal capital asset pricing model. Econometrica, 41(5), 867–887. https://doi.org/10.2307/1913811
Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. Penguin Press.
Pascovich, E. (2018). The devil’s advocate in intelligence: The Israeli experience. Intelligence and National Security, 33(6), 854–865. https://doi.org/10.1080/02684527.2018.1470062
Poyser, O. (2018). Herding behavior in cryptocurrency markets. SSRN Working Paper. https://doi.org/10.2139/ssrn.3092427
Prechter, R. R., Jr., & Parker, W. D. (2007). The financial/economic dichotomy in social behavioral dynamics: The socionomic perspective. Journal of Behavioral Finance, 8(2), 84–108. https://doi.org/10.1080/15427560701381028
Ranaldo, A., Söderlind, P., & Wagner, A. (2025). Crypto investor attention and market fragility. Journal of Financial Economics, 158(1), 103– 121. https://doi.org/10.1016/j.jfineco.2024.12.004
Sergi, B. S., Popkova, E., & Bogoviz, A. (2024). Herd behavior, social media sentiment, and cryptocurrency price dynamics. Technological Forecasting & Social Change, 198, 122123. https://doi.org/10.1016/j.techfore.2023.122123
Shiller, R. J. (2015). Irrational exuberance (3rd ed.). Princeton University Press. https://doi.org/10.2307/j.ctt1287kz5
Shleifer, A. (2000). Inefficient markets: An introduction to behavioral finance. Oxford University Press.
Sunstein, C. R. (2002). The law of group polarization. Journal of Political Philosophy, 10(2), 175–195. https://doi.org/10.1111/1467- 9760.00148
Sundarasen, S., & Saleem, F. (2025). From tweets to trades: A bibliometric and systematic review of social media’s influence on cryptocurrency. International Journal of Financial Studies, 13(2), 87. https://doi.org/10.3390/ijfs13020087
Tetlock, P. C. (2007). Giving content to investor sentiment: The role of media in the stock market. The Journal of Finance, 62(3), 1139–1168. https://doi.org/10.1111/j.1540-6261.2007.01232.x
Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297–323. https://doi.org/10.1007/BF00122574
Urgenc, O. A., & Tas, O. (2024). Social media sentiment and its effects on cryptocurrency price volatility. PressAcademia Procedia, 20(1), 1– 4. https://doi.org/10.17261/Pressacademia.2024.1915
Watts, D. J., & Dodds, P. S. (2007). Influentials, networks, and public opinion formation. Journal of Consumer Research, 34(4), 441–458. https://doi.org/10.1086/518527
Wang, G.-J., Xie, C., & Zhao, L. (2024). Social media emotions and cryptocurrency volatility: New evidence from high-frequency data. Journal of Economic Behavior & Organization, 219, 350–366. https://doi.org/10.1016/j.jebo.2024.04.018
Yousaf, I., Yarovaya, L., & Mirza, N. (2023). Energy cryptocurrencies: Assessing connectedness with other asset classes. Finance Research Letters, 51, 103373. https://doi.org/10.1016/j.frl.2023.103373

Details

Primary Language

English

Subjects

Finance

Journal Section

Research Article

Authors

Lyu Jia-Ying
0000-0002-2261-8691
China

Publication Date

December 31, 2025

Submission Date

November 2, 2025

Acceptance Date

December 20, 2025

Published in Issue

Year 2025 Volume: 12 Number: 2

DOI

https://doi.org/10.17261/Pressacademia.2025.2008

IZ

https://izlik.org/JA83RZ49BF

Cite

RIS / Bibtex

APA

Jia-Ying, L. (2025). THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS. Journal of Economics Finance and Accounting, 12(2), 162-176. https://doi.org/10.17261/Pressacademia.2025.2008

AMA

1.Jia-Ying L. THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS. JEFA. 2025;12(2):162-176. doi:10.17261/Pressacademia.2025.2008

Chicago

Jia-Ying, Lyu. 2025. “THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS”. Journal of Economics Finance and Accounting 12 (2): 162-76. https://doi.org/10.17261/Pressacademia.2025.2008.

EndNote

Jia-Ying L (December 1, 2025) THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS. Journal of Economics Finance and Accounting 12 2 162–176.

IEEE

[1]L. Jia-Ying, “THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS”, JEFA, vol. 12, no. 2, pp. 162–176, Dec. 2025, doi: 10.17261/Pressacademia.2025.2008.

ISNAD

Jia-Ying, Lyu. “THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS”. Journal of Economics Finance and Accounting 12/2 (December 1, 2025): 162-176. https://doi.org/10.17261/Pressacademia.2025.2008.

JAMA

1.Jia-Ying L. THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS. JEFA. 2025;12:162–176.

MLA

Jia-Ying, Lyu. “THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS”. Journal of Economics Finance and Accounting, vol. 12, no. 2, Dec. 2025, pp. 162-76, doi:10.17261/Pressacademia.2025.2008.

Vancouver

1.Lyu Jia-Ying. THE ABILENE PARADOX AND COLLECTIVE IRRATIONALITY IN CRYPTOCURRENCY MARKETS: A SOCIAL MEDIA SENTIMENT ANALYSIS. JEFA. 2025 Dec. 1;12(2):162-76. doi:10.17261/Pressacademia.2025.2008