Abstract
A recurring problem with the study of sexual fantasy is that of social desirability bias. Study participants may report fantasies that are consistent with general societal expectations of fantasy content, as opposed to themes characterized by their actual fantasies. The wide availability of erotic material on the Internet, however, facilitates the study of sexual fantasy narratives as they are anonymously expressed and viewed online. By extracting approximately 250,000 text-based erotic fantasies from a user-generated website, we sought to examine “real-world” sexual fantasies, determine the themes that were typical of these narratives, and explore the relationship between themes and story popularity (as assessed by story views per day). A principal components analysis identified 20 themes that commonly occurred across the massive corpus, and a path analysis revealed that these themes played a significant role in predicting the popularity of the sexual fantasy narratives. In particular, the empirically identified themes reflecting familial words (e.g., mother, father) and colloquial sexual words (e.g., cock, fuck) were predictive of story popularity. Other themes identified included those not obviously erotic, such as those consisting of words reflecting domesticity (e.g., towel, shower) and colors (e.g., brown, blue). By analyzing a sexual fantasy corpus of unprecedented size, this study offers unique insight into both the content of sexual fantasies and the popularity of that content.
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References
Ahlers, C. J., Shaefer, G. A., Mundt, I. A., Roll, S., Englert, H., Willich, S. N., & Beier, K. M. (2011). How unusual are the content of paraphilias? Paraphilia-associated sexual arousal patterns in a community-based sample of men. Journal of Sexual Medicine, 8(5), 1362–1370.
Bargh, J. A., McKenna, K. Y. A., & Fitzsimons, G. M. (2002). Can you see the real me? Activation and expression of the “true self” on the Internet. Journal of Social Issues, 58(1), 33–48.
Benoint, K., Watanabe, K., Nulty, P., Obeng, A., Wang, H., Lauderdale, B., & Lowe, W. (2017). quanteda: Quantitative analysis of textual data. R Package version: 0.9.9-65.
Bivona, J., & Critelli, J. (2009). The nature of women’s rape fantasies: An analysis of prevalence, frequency, and contents. Journal of Sex Research, 46(1), 33–45.
Boyd, R. L. (2014). MEH: Meaning extraction helper (version 1.4.15) [Software]. https://meh.ryanb.cc.
Boyd, R. L., Wilson, S. R., Pennebaker, J. W., Kosinski, M., Stillwell, D. J., & Mihalcea, R. (2015). Values in words: Using language to evaluate and understand personal values. In D. Quercia (Ed.), Proceedings of the ninth international AAAI conference on web and social media (pp. 31–40). Palo Alto, California: The AAAI Press.
Briere, J., & Runtz, M. (1989). University males’ sexual interest in children: Predicting potential indices of “pedophilia” in a nonforensic sample. Child Abuse and Neglect, 13(1), 65–75.
Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York, NY: Guilford Publications.
Burnham, K. P., & Anderson, D. R. (1998). Information theory and log-likelihood models: A basis for model selection and inference. In Model selection and inference (pp. 32–74). New York, NY: Springer.
Chung, C. K., & Pennebaker, J. W. (2008). Revealing dimensions of thinking in open-ended self-descriptions: An automated meaning extraction method for natural language. Journal of Research in Personality, 42(1), 96–132.
Dodou, D., & de Winter, J. C. (2014). Social desirability is the same in offline, online, and paper surveys: A meta-analysis. Computers in Human Behavior, 36, 487–495.
Dombert, B., Schmidt, A. F., Banse, R., Briken, P., Hoyer, J., Neutze, J., & Osterheider, M. (2016). How common is men’s self-reported sexual interest in prepubescent children? Journal of Sex Research, 53(2), 214–223.
Ellis, B. J., & Symons, D. (1990). Sex differences in sexual fantasy: An evolutionary psychological approach. Journal of Sex Research, 27(4), 527–555.
Field, A. (2009). Discovering statistics using SPSS. Thousand Oaks, CA: Sage Publications.
Frohmuth, M. E., Burkhart, B. R., & Jones, C. W. (1991). Hidden child molestation: An investigation of adolescent perpetrators in a nonclinical sample. Journal of Interpersonal Violence, 6(3), 376–384.
Gilden, A. (2016). Punishing sexual fantasy. William & Mary Law Review, 58, 419–491.
Gold, S. R., Balzano, B. F., & Stamey, R. (1991). Two studies of females’ sexual force fantasies. Journal of Sex Education and Therapy, 17(1), 15–26.
Greaney, D. (Writer) & Afflek, N. (Director). (1998). This little Wiggy [Television series episode]. In M. Groening (Ed.), The Simpsons. Los Angeles: Gracie Films.
Handy, A. B., Wassersug, R. J., Ketter, J. T., & Johnson, T. W. (2015). The sexual side of castration narratives: Fiction written by and for eunuchs and eunuch “wannabes”. Canadian Journal of Human Sexuality, 24(2), 151–159.
Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185.
Hornik, K., Mair, P., Rauch, J., Geiger, W., Buchta, C., & Feinerer, I. (2013). The textcat package for n-gram based text categorization in R. Journal of Statistical Software, 52(6), 1–17.
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.
Joinson, A. N. (2001). Self-disclosure in computer-mediated communication: The role of self-awareness and visual anonymity. European Journal of Social Psychology, 31(2), 177–192.
Joyal, C. C., & Carpentier, J. (2017). The prevalence of paraphilic interests and behaviors in the general population: A provincial survey. Journal of Sex Research, 54(2), 161–171.
Joyal, C. C., Cossette, A., & Lapierre, V. (2015). What exactly is an unusual sexual fantasy? Journal of Sexual Medicine, 12(2), 328–340.
Kincaid, J., Fishburne Jr., R., Rogers, R. L., & Chissom, B. S. (1975). Derivation of new readability formulas (auomated readability index, fog count, and flesch reading ease formula) for Navy enlisted personnel (No. RBR-8-75). Naval Technical Training Command Millington TN Research Branch.
Leitenberg, H., & Henning, K. (1995). Sexual fantasy. Psychological Bulletin, 117(3), 469–496.
Maniglio, R. (2010). The role of deviant sexual fantasy in the etiopathogenesis of sexual homicide: A systematic review. Aggression and Violent Behavior, 15(4), 294–302.
Pornhub’s 2016 Year in Review. (2017). Retrieved September 5, 2017, from https://www.pornhub.com/insights/2016-year-in-review.
R Core Team. (2017). R: A language and environment for statistical computing [Computer software]. Vienna: R Foundation for Statistical Computing.
Salton, G., & Smith, M. (1989). On the application of syntactic methodologies in automatic text analysis. ACM SIGIR Forum, 23, 137–150.
Seifert, K., Boulas, J., Huss, M. T., & Scalora, M. J. (2017). Response bias on self-report measures of sexual fantasies among sexual offenders. International Journal of Offender Therapy and Comparative Criminology, 61(3), 269–281.
Stanton, A. M., Boyd, R. L., Pulverman, C. S., & Meston, C. M. (2015). Determining women’s sexual self-schemas through advanced computerized text analysis. Child Abuse and Neglect, 46, 78–88.
Strassberg, D. S., & Lowe, K. (1995). Volunteer bias in sexuality research. Archives of Sexual Behavior, 24(4), 369–382.
Suler, J. (2004). The online disinhibition effect. Cyberpsychology & Behavior, 7(3), 321–326.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Needham Heights, MA: Allyn & Bacon.
United States v. Curtin, 489 F.3d 935, 958-59 (9th Cir., 2007).
Weisband, S., & Kiesler, S. (1996). Self disclosure on computer forms: Meta-analysis and implications. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 3–10). New York, New York: ACM Publications.
Williams, K. M., Cooper, B. S., Howell, T. M., Yuille, J. C., & Paulhus, D. L. (2009). Inferring sexually deviant behavior from corresponding fantasies: The role of personality and pornography consumption. Criminal Justice and Behavior, 36(2), 198–222.
Wolf, M., Chung, C. K., & Kordy, H. (2010). Inpatient treatment to online aftercare: E-mailing themes as a function of therapeutic outcomes. Psychotherapy Research, 20(1), 71–85.
Woodworth, M., Freimuth, T., Hutton, E. L., Carpenter, T., Agar, A. D., & Logan, M. (2013). High-risk sexual offenders: An examination of sexual fantasy, sexual paraphilia, psychopathy, and offence characteristics. International Journal of Law and Psychiatry, 36(2), 144–156.
Wurtele, S. K., Simons, D., & Moreno, T. (2014). Sexual interest in children among an online sample of men and women: Prevalence and correlates. Sexual Abuse: A Journal of Research and Treatment, 26, 546–568.
Yarkoni, T. (2010). Personality in 100,000 words: A large-scale analysis of personality and word use among bloggers. Journal of Research in Personality, 44(3), 363–373.
Zhang, Y., Chen, W., Wang, D., & Yang, Q. (2011). User-click modeling for understanding and predicting search-behavior. In Proceedings of the 17th ACM SIGKDD International conference on knowledge discovery and data mining-KDD’11, (p. 1388). New York: ACM Publications.
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This work was supported in part by the Middlebury College Digital Liberal Arts Initiative.
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Seehuus, M., Stanton, A.M. & Handy, A.B. On the Content of “Real-World” Sexual Fantasy: Results From an Analysis of 250,000+ Anonymous Text-Based Erotic Fantasies. Arch Sex Behav 48, 725–737 (2019). https://doi.org/10.1007/s10508-018-1334-0
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DOI: https://doi.org/10.1007/s10508-018-1334-0