Listening, Watching, and Reading: The Structure and Correlates of Entertainment Preferences

Abstract

People spend considerable amounts of time and money listening to music, watching TV and movies, and reading books and magazines, yet almost no attention in psychology has been devoted to understanding individual differences in preferences for such entertainment. The present research was designed to examine the structure and correlates of entertainment genre preferences. Analyses of the genre preferences of over 3,000 individuals revealed a remarkably clear factor structure. Using multiple samples, methods, and geographic regions, data converged to reveal five entertainment-preference dimensions: Communal, Aesthetic, Dark, Thrilling, and Cerebral. Preferences for these entertainment dimensions were uniquely related to demographics and personality traits. Results also indicated that personality accounted for significant proportions of variance in entertainment preferences over and above demographics. The results provide a foundation for developing and testing hypotheses about the psychology of entertainment preferences. Keywords Personality; Media; Entertainment; PreferencesIn an average week, the typical American spends approximately 38 hours watching television shows and movies, 8 hours reading books, magazines, and newspapers, and 18 hours listening to recorded music and radio (Motion Picture Association of America, 2007). Assuming the average person sleeps eight hours a night, people spend roughly 55% of their waking hours attending to entertainment media. Americans spend almost as much of their annual incomes on entertainment as they do on health care, and more money is spent on entertainment than on education, personal care, and charitable donations (United States Bureau of Labor, 2008). Of the money spent on entertainment, cable and satellite TV account for 39%, books, magazines, and newspapers for 23%, movie consumption for 19%, recorded music for 6%, and Internet, video games, mobile content, and satellite radio combined for 13% (Motion Picture Association of America, 2007). NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptConsidering that entertainment media are nearly ubiquitous, it is astonishing that they have received so little attention in personality and social psychology. Indeed, of the nearly 15,000 articles published between 1932 and 2008 in the Journal of Personality and Social Psychology, Journal of Personality, and Personality and Social Psychology Bulletin, "television," "movie," "film," "music," "book," "magazine," or "media" were listed as subject headings in only 90 of them-a mere 0.6%. Many psychologists have argued that researchers need to broaden their research foci and pay more attention to ordinary aspects of people's daily lives so that we can develop an understanding of social behavior that is more ecologically sensitive (e.g., Funder, 2001;Rozin, 2001). Entertainment is undoubtedly important to people and permeates many aspects of social life, yet we know little about it. The present work was designed to explore the landscape of this undeveloped te...

Music through the ages: Trends in musical engagement and preferences from adolescence through middle adulthood.

“…The results from the analyses yield a factor stmcture that resembles the MUSIC model reported in Rentfrow, Goldberg, and Levitin (2011), Rentfrow et al (2012), and Rentfrow, Goldberg, and Zilca (2011). The factor loadings in the first data column of Table 1 show large loadings for electronica/dance, world, and new age, styles that are perceived as relaxing, unaggressive, and atmospheric, qualities consistent witii the Mellow preference dimension.…”

How “outsider” do we like our art?: Influence of artist background on perceptions of warmth, creativity, and likeability.

“…Rentfrow, Goldberg, and Zilca (2011) found a highbrow/lowbrow split regardless of the entertainment medium (including books, films, music, or TV). They also found a five-factor solution, with two factors relating to the highbrow preference (aesthetic and cerebral) and three for lowbrow (communal, dark, and thrilling).…”

On the Use of Cross-Domain User Preferences and Personality Traits in Collaborative Filtering

“…This model establishes five dimensions (traits) to describe personality: openness, conscientiousness, extraversion, agreeableness and neuroticism. Recent research has shown that correlations between user preferences and personality factors exist in certain domains [3,9], and that these correlations can be used to enhance personalized recommendations [7]. For instance, Hu and Pu [8] presented a method in which user similarities are computed as the Pearson's coefficient of their FF scores, and combined this approach with rating-based similarities to improve CF.…”

“…Recently, new sources of side information have been explored to enrich user models for collaborative filtering (CF). In particular, it has been shown that people with similar personality traits are likely to have similar preferences [3,9], and that correlations between user preferences and personality traits allow improving personalized recommendations [8,12]. Moreover, cross-domain recommendation methods [4] have been shown to be effective in target domains, by exploiting user preferences in other source domains [1,2,10].…”