Sexual Experiences and Beliefs Vary by Patterns of Pornography Genre Preferences Among Women.

Pornography use is multidimensional, yet most studies of the topic use variable-oriented methods (e.g., frequency of use) that reduce the experience to a single dimension. In this study, we sought to identify different multidimensional patterns of pornography genre preferences among a sample of women (n = 206) and examine how those patterns are differentially associated with sexual experiences and beliefs examined in previous literature. Latent Class Analysis uncovered four patterns (or classes): Heterogeneous (39%), Traditionally Feminine (27%), Female Pleasure (23%) and Rough/violent (11%). Class membership was differentially predicted by prior sexual victimization, sexual esteem, and diverse sexual experiences while controlling for frequency of use. These findings suggest that genre preference could account for much of the mixed findings of prior work that measured pornography use with unidimensional approaches.

Women Keep it Real: Avatar Gender Choice in League of Legends.

This article examines avatar gender choice within a competitive context in which avatar gender is not equivalent across functions. In data from the game League of Legends (n = 15,392) reflecting >5 million avatar gender choices, women were found to have stronger preferences for avatar gender consistency than men. Furthermore, women tended to choose female avatars at twice the available rate offered by the game, whereas men chose male avatars at a rate approximately the same as the proportion offered. These findings support the argument that women experience more pressure than men do to perform their gender identities overtly, even in competitive games where avatar choice is mostly functional and avatar gender is fixed within specific characters. A practical implication is that by offering a wider range of female avatar and character options, game designers could likely attract greater female audiences without a significant loss of male players.

Virtual muscularity: a content analysis of male video game characters.

The 150 top-selling video games were content analyzed to study representations of male bodies. Human males in the games were captured via screenshot and body parts measured. These measurements were then compared to anthropometric data drawn from a representative sample of 1120 North American men. Characters at high levels of photorealism were larger than the average American male, but these characters did not mirror the V-shaped ideal found in mainstream media. Characters at low levels of photorealism were also larger than the average American male, but these characters were so much larger that they appeared cartoonish. Idealized male characters were more likely to be found in games for children than in games for adults. Implications for cultivation theory are discussed.