There are two conflicting perspectives regarding the relationship between profanity and dishonesty. These two forms of norm-violating behavior share common causes and are often considered to be positively related. On the other hand, however, profanity is often used to express one’s genuine feelings and could therefore be negatively related to dishonesty. In three studies, we explored the relationship between profanity and honesty. We examined profanity and honesty first with profanity behavior and lying on a scale in the lab (Study 1; N = 276), then with a linguistic analysis of real-life social interactions on Facebook (Study 2; N = 73,789), and finally with profanity and integrity indexes for the aggregate level of U.S. states (Study 3; N = 50 states). We found a consistent positive relationship between profanity and honesty; profanity was associated with less lying and deception at the individual level and with higher integrity at the society level.

Frankly my dear, I don’t give a damn. Gone with the Wind (1939)

Profane as it is, this memorable line by the character Rhett Butler in the film Gone with the Wind profoundly conveys Butler’s honest thoughts and feelings. However, it was the use of this profane word that led to a US$5,000 fine against the film’s production for violating the Motion Picture Production Code. This example reveals the conflicting attitudes that most societies hold toward profanity, reflected in a heated debate taking place in online forums and media in recent years—with passionate views on both sides. For example, the website debate.org, which conducts online polls and elicits general public opinions on popular online debates, has many comments on the issue, with a 50–50 tie between the two views (Are people who swear more honest?, 2015). This public debate reflects an interesting question and mirrors the academic discussion regarding the nature of profanity. On the one hand, profane individuals are widely perceived as violating moral and social codes and thus deemed untrustworthy and potentially antisocial and dishonest (Jay, 2009). On the other hand, profane language is considered as more authentic and unfiltered, thus making its users appear more honest and genuine (Jay, 2000). These opposing views on profanity raise the question of whether profane individuals tend to be more or less dishonest.

Method Participants and Procedure A total of 307 participants were recruited online using Amazon Mechanical Turk. Of the sample, 31 participants failed attention checks (10%) and were excluded from the analysis, leaving a sample of 276 (M age = 40.71, SD age = 12.75; 171 females). The exclusion of participants had no significant impact on the reported effect sizes or p values below. Participants self-reported profanity use in everyday life: given the opportunity to use profanity, rated reasons for the use of profanity, and answered a lie scale. Measures Profanity use behavioral measure In 2 items, participants were asked to list their most commonly used and favorite profanity words: “Please list the curse words you [1 – use; 2 – like] the most (feel free, don’t hold back).” By giving participants an opportunity to curse freely, we expected that the daily usage and enjoyment of profanity would be reflected in the total number of curse words written. Participants’ written profanity was counted and coded by the first author and a coder unrelated to the project, who was unaware of the study hypotheses and data structure. The interrater reliability was .91 (95% confidence interval [CI] [.87, .94]) for most commonly used curse words and .93 (95% CI [.91, .97]) for favorite curse words, indicating a very high level of agreement. Profanity self-reported use To supplement the behavioral measures, we also added self-reported use of profanity. Participants self-reported their everyday use of profanity (Rassin & Muris, 2005) using 3 items: “How often do you curse (swear/use bad language)” (1) “verbally in person (face to face),” (2) “in private (no one around),” and (3) “in writing (e.g., texting/messaging/posting online/emailing”; 1 = never, 2 = once a year or less, 3 = several times a year, 4 = once a month, 5 = 2–3 times a month, 6 = once a week, 7 = 2–3 times a week, 8 = 4–6 times a week, 9 = daily, 10 = a few times a day; α = .84). Reasons for profanity use Following Rassin and Muris (2005), we also asked participants to rate reasons for their use of profanity (0 = never a reason for me to swear; 5 = very often a reason for me to swear) and asked questions regarding the general perceived reasons for using profanity (0 = not at all; 5 = to a very large extent; see Online Supplemental Materials). Honesty Honesty was measured using the Lie subscale of the Eysenck Personality Questionnaire Revised short scale (Eysenck, Eysenck, & Barrett, 1985). The Lie subscale is one of the most common measures for assessing individual differences in lying for socially desirable responding (Paulhus, 1991). The Lie scale includes 12 items, such as “If you say you will do something, do you always keep your promise no matter how inconvenient it might be?” and “Are all your habits good and desirable ones?” (dichotomous Yes/No scale). In these examples, positive answers are considered unrealistic and therefore most likely a lie (α = .79). The Lie scale was reversed for the honesty measure.

Results A scatterplot of profanity and integrity rates for all states is provided in Figure 2. We found a positive relationship between profanity and integrity on a state level (N = 50; r = .35, p = .014; CI [.08, .57]). States with a higher profanity rate had a higher integrity score.2 For example, two of the three states with the highest profanity rate, Connecticut and New Jersey, were also two of the three states with the highest integrity scores on the index. Download Open in new tab Download in PowerPoint We also conducted a spatial regression analysis to address possible spatial-dependence regional confounds (Ward & Gleditsch, 2008). We calculated spatial distance matrices (Merryman, 2008) for the distance between states’ centroids using the following formula for Euclidean distance between State A and State B (y and x denote the y coordinate and x coordinate, respectively): d ( x A , y A ; x B , y B ) = ( y A − y B ) 2 + ( x A − x B ) 2 . We then inverted the distances (1/X) to form a proximity measure, multiplied the proximity matrix by the state profanity column, and divided by the sum to create a measure of spatial lag—a spatial weighted profanity per each state (Webster & Duffy, 2016). Excluding Hawaii and Alaska for their geographical isolation, the spatial profanity measure had a correlation of r = .55 with the state profanity measure (n = 48; p < .001; CI [.32, .72]; Moran I statistic = .15, p < .001), indicative of spatial dependence. After controlling for the spatial profanity, the partial correlation between profanity and integrity was r = .33 (p = .025, CI [.05, .56]).

General Discussion We examined the relationship between the use of profanity and dishonesty and showed that profanity is positively correlated with honesty at an individual level and with integrity at a society level. Table 5 provides a summary of the results. Study 1 showed that participants with higher profanity use were more honest on a lie scale, and in Study 2, profanity was associated with more honest language patterns in Facebook status updates. In Study 3, state-level profane language usage was positively related to state-level integrity. Table 5. Summary of the Results. View larger version Challenges in Studying Profanity and Dishonesty in Naturalistic Settings The empirical investigation of the relationship between dishonesty and profanity poses a unique challenge. The behavioral ethics literature has been successful in devising ways to examine unethical behavior in the lab, yet observing dishonesty and unethical behavior in the field remains an ongoing challenge, and so far only a few studies were able to devise innovative methods to overcome that challenge (e.g., Hofmann et al., 2014; Piff, Stancato, Côté, Mendoza-Denton, & Keltner, 2012). The indirect linguistic approach for the detection of dishonesty with an analysis of spoken and written language patterns paves the way for more behavioral ethics research on actual dishonest behavior in the field. Unlike behavioral ethics, the study of profanity is still very much in its infancy (Jay, 2009). Profanity is a much harder construct to measure and even more difficult to effectively elicit or manipulate, whether it is in the lab or in the field. The relatively low use rates of profanity decrease even further when people know that they are observed or that their behavior is studied. Therefore, to be able to gain an understanding of profanity use, it is important that the behavior observed is genuine and in naturalistic settings. The current investigation has been able to address this challenge by applying a linguistic analysis approach to a unique large-scale naturalistic behavior data set. The linguistic approach to detecting dishonesty used in Study 2 has been used and verified in a number of previous studies (e.g., Feldman et al., 2015; Slatcher et al., 2007). In Study 2, the linguistic analysis showed that men tended to be more dishonest than women, which is in line with a large body of literature presenting similar findings (Childs, 2012; Dreber & Johannesson, 2008; Friesen & Gangadharan, 2012). Also, those with larger networks had a higher likelihood for dishonesty and a lower likelihood for profanity, which supports the notion of dishonesty online as a means of creating a more socially desirable profile. Both findings contribute to the construct validity of the linguist honesty measure by demonstrating previously established nomological networks. The consistency in the direction and effect size of the profanity–honesty relationship across the three studies further raises confidence in this approach to measuring dishonesty. Extending to Society Level Our research offers a first look at the use of profanity at a society level. Using the large-scale sample of American participants from Study 2, we were able to calculate state-level rates of profanity for use in Study 3. Addressing calls for psychological research to attempt to examine the social implications of psychological findings (Back, 2015; Back & Vazire, 2015), we used this measure in order to examine whether the positive relationship between profanity and honesty found at the individual level could be extended to the society level. Such an attempt involves many challenges, as there are many variables that may intervene or offer competing explanations for a detected relationship. Yet we believe that this is an important first attempt to provide a baseline for further investigation. The consistent findings across the studies suggest that the positive relation between profanity and honesty is robust and that the relationship found at the individual level indeed translates to the society level. Implications and Future Directions We briefly note several limitations in the current research and these are further discussed in the Online Supplemental Materials with implications and future directions. First, the three studies were correlational, thus preventing us from drawing any causal conclusions. Second, the dishonesty we examined in Studies 1 and 2 was mainly about self-promoting deception to appear more desirable to others rather than blunt unethical behavior. We therefore caution that the findings should not be interpreted to mean that the more a person uses profanity, the less likely he or she will engage in more serious unethical or immoral behaviors. Third, the measures in Study 2 were proxies using an aggregation of linguistic analysis of online behavior using Facebook over a long period of time. Finally, Simpson’s Paradox (Simpson, 1951) points to conceptual and empirical differences in testing a relationship on different levels of analysis, and therefore the state-level findings of Study 3 are conceptually broader than the findings in Studies 1 and 2. These limitations notwithstanding, our research is a first step in exploring the profanity–honesty relationship, and we believe that the consistent effect across samples, methodology, and levels of analysis contributes to our understanding of the two constructs and paves the way for future research. Future studies could build on our findings to further study the profanity–honesty relationship using experimental methods to establish causality and incorporating real-life behavioral measures with a wider range of dishonest conduct including unethical behavior.

Conclusion We set out to provide an empirical answer to competing views regarding the relationship between profanity and honesty. In three studies, at both the individual and society level, we found that a higher rate of profanity use was associated with more honesty. This research makes several important contributions by taking a first step to examine profanity and honesty enacted in naturalistic settings, using large samples, and extending findings from the individual level to a look at the implications for society.

Authors’ Note

Gilad Feldman developed the paper concept, performed testing, data analysis, results interpretation, and writing. Huiwen Lian contributed to concept framing, writing, and provided input and feedback throughout. Michal Kosinski and David Stillwell built the myPersonality platform used in Studies 2 and 3, collected and coded the data, and performed the linguistic analyses. All authors provided critical revisions and approved the article for submission. M. Kosinski and D. Stillwell were equally contributed to this work. Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article. Supplemental Material

The supplemental material is available in the online version of the article.

Notes 1.

The Online Supplemental Materials include further details and a report of the results using the original equation of negative emotions including anger (r = .02, p < .001; 95% CI [.01, .03]; with controls: partial r = .04, p < .001; 95% CI [.03, .05]). 2.

We noted problems in using crime and conviction rates in the methods but ran several robustness checks. Higher state average of profanity use was negatively correlated with state rates of property crime (r = −.30, p = .032), burglary (r = −.31, p = .029), larceny theft (r = −.34, p = .015), and rape (r = −.24, p = .093)—obtained from the Federal Bureau of Investigation website.