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Distant reading case study "Jeffrey Epstein" ​

Analysing networks of exploitation ​

Jeffrey Edward Epstein was an American financier and sex offender, who died in prison in 2019. The Epstein abuse cases made international news because Epstein, supported by his partner Ghislaine Maxwell, build a high-profile network of rich and famous men exploiting vulnerable women, above all young girls and women from difficult backgrounds. Feminist analysis of how the Epstein case was discussed in 2019 when reporting peaked can help us understand how societal structures of power and privilege enable such exploitation. We can also reflect on systemic gender inequalities and the role of female collaborators in predatory behaviour.

Reviews to the Devil in the Darkness podcast ​

One internationally successful podcast on the Epstein case was Devil in the Darkness, released in autumn 2019. Monika has scraped reviews of this podcast as a training data set to practice distant reading and feminist theory. This dataset offers insights into listeners' attitudes towards masculinity, issues of privilege, justice, and morality.

Questions for data analysis ​

In your data analysis, you can try and follow the steps outlined in Skill 2.1. Voyant Tools and Skills 2.2. Case Study. You may also want to discuss the following questions with the other students:

  • What do listeners think about power structures behind the exploitation of vulnerable individuals, particularly women?
  • In what ways does the media's portrayal of the Epstein case reflect and reinforce societal attitudes towards victims of sexual violence?
  • What role does intersectionality play in understanding the listener reactions to the Epstein case?
  • What do listeners think about the role of law enforcement and the judicial system in preventing abuse and punishing abusers?
  • What implications does the Epstein case have for feminist activism and advocacy regarding sexual violence and trafficking?

Please make sure to use several different tools in Voyant. You can also scrape your own additional data for comparative analysis.