The political, psychological, and social correlates of cryptocurrency ownership

Abstract

Cryptocurrency is a digital asset secured by cryptography that has become a popular medium of exchange and investment known for its anonymous transactions, unregulated markets, and volatile prices. Given the popular subculture of traders it has created, and its implications for financial markets and monetary policy, scholars have recently begun to examine the political, psychological, and social characteristics of cryptocurrency investors. A review of the existing literature suggests that cryptocurrency owners may possess higher-than-average levels of nonnormative psychological traits and exhibit a range of non-mainstream political identities. However, this extant literature typically employs small nonrepresentative samples of respondents and examines only a small number of independent variables in each given study. This presents the opportunity for both further testing of previous findings as well as broader exploratory analyses including more expansive descriptive investigations of cryptocurrency owners. To that end, we polled 2,001 American adults in 2022 to examine the associations between cryptocurrency ownership and individual level political, psychological, and social characteristics. Analyses revealed that 30% of our sample have owned some form of cryptocurrency and that these individuals exhibit a diversity of political allegiances and identities. We also found that crypto ownership was associated with belief in conspiracy theories, "dark" personality characteristics (e.g., the "Dark Tetrad" of narcissism, Machiavellianism, psychopathy, and sadism), and more frequent use of alternative and fringe social media platforms. When examining a more comprehensive multivariate model, the variables that most strongly predict cryptocurrency ownership are being male, relying on alternative/fringe social media as one's primary news source, argumentativeness, and an aversion to authoritarianism. These findings highlight numerous avenues for future research into the people who buy and trade cryptocurrencies and speak to broader global trends in anti-establishment attitudes and nonnormative behaviors.

Fig 1. Distribution of responses (yes/no) to question asking if participants currently own or have owned cryptocurrency.

Bars indicate the percentage of participants who selected each response. N = 2,001.

Fig 2. Associations with demographics variables.

Point-biserial correlations between cryptocurrency ownership and various demographic categories. Error bars represent 95% confidence intervals. N = 2,001.

Fig 3. Associations with variables related to conspiracy thinking.

Point-biserial correlations between cryptocurrency ownership and variables related to thinking styles, conspiracy beliefs, and attitudes toward science. Error bars represent 95% confidence intervals. N = 2,001.

Fig 4. Associations with left/right political orientations and attitudes.

Point-biserial correlations between cryptocurrency ownership and ratings of traditional left/right political orientations and “feeling thermometer (0–100) ratings of various political figures and groups. Error bars represent 95% confidence intervals. N = 2,001.

Fig 5. Associations with non-left/right political orientations and attitudes.

Point-biserial correlations between cryptocurrency ownership and ratings of non-left/right political orientations and “feeling thermometer (0–100) ratings of various political figures and groups. Error bars represent 95% confidence intervals. N = 2,001.

Fig 6. Associations with left/right political orientations and attitudes.

Point-biserial correlations between cryptocurrency ownership and ratings of traditional left/right political orientations and “feeling thermometer (0–100) ratings of various political figures and groups. Error bars represent 95% confidence intervals. N = 2,001.

Fig 7. Associations with interpersonal and political behaviors.

Point-biserial correlations between cryptocurrency ownership and various interpersonal and political behaviors. Error bars represent 95% confidence intervals. N = 2,001.

Fig 8. Associations with personality, emotional, and motivational attributes.

Point-biserial correlations between cryptocurrency ownership and personality, emotional, and motivational variables. Error bars represent 95% confidence intervals. N = 2,001.

Fig 9. Associations with information environment.

Point-biserial correlations between cryptocurrency ownership and various online and offline group (A) and individual (B) sources of news information. Error bars represent 95% confidence intervals. N = 2,001.

Fig 10. Logistic regression predicting cryptocurrency ownership from demographics, thinking styles and intellectual attitudes, personality characteristics, and media environment.

Coefficients are log odds. Error bars represent 95% confidence intervals. N = 2,001.

Fig 11. Logistic regression predicting cryptocurrency ownership from individual online media sources.

Coefficients are log odds. Error bars represent 95% confidence intervals. N = 2,001.