Deepfake pornography as a male gaze on fan culture

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Authors: Inna Suvorova

Published: 2022-02-01 12:30:27+00:00

AI Summary

This essay examines the intersection of deepfake technology and fan culture, arguing that deepfake pornography, while often viewed through the lens of celebrity studies, can be understood as a form of fanfiction produced and consumed primarily by men, unlike traditional fanfiction which is largely created by and for women.

Abstract

This essay shows the impact of deepfake technology on fan culture. The innovative technology provided the male audience with an instrument to express its ideas and plots. Which subsequently led to the rise of deepfake pornography. It is often seen as a part of celebrity studies; however, the essay shows that it could also be considered a type of fanfic and a product of participatory culture, sharing community origin, exploitation by commercial companies and deep sexualisation. These two branches of fanfic evolution can be connected via the genre of machinima pornography. Textual fanfics are mainly created by females for females, depicting males; otherwise, deepfake pornography and machinima are made by males and for males targeting females.

Key findings

Deepfake pornography shares similarities with fanfiction in terms of participatory culture and sexual themes, but differs significantly in its audience (primarily male creators and consumers) and societal reception. The paper suggests deepfake pornography can be considered a type of fanfiction, albeit one distinct from traditional forms due to gender dynamics and the controversial nature of the medium.

Approach

The paper uses a qualitative approach, analyzing deepfake pornography within the broader context of fan culture, comparing and contrasting it with traditional fanfiction and machinima pornography. It explores similarities in participatory culture and sexualization while highlighting differences in audience demographics and societal perception.

Datasets

The paper does not use a dataset in the traditional sense; instead, it draws on examples from various online sources, including websites hosting fanfiction and deepfakes, news articles, and academic literature.

Model(s)

UNKNOWN

Author countries

United Kingdom

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