JOURNAL ARTICLE
In the Dark: The Afterlife of a Horror Hoax.
Published In: Gothic Studies, 2023, v. 25, n. 1. P. 42 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Kvistad, Erika 3 of 3
Abstract
In the Dark, a 2007 webseries directed by Andrew Cull that purports to be the YouTube channel of a young woman documenting a haunting in her apartment, is arguably the first horror hoax webseries on YouTube. Two decades after the popular rise of two horror media traditions that make use of the storytelling power of hoaxes, the found footage horror film and creepypasta, this article returns to In the Dark as an early work that draws on both these modes and asks: what happens when a hoax gets old? If the credibility of a hoax is inherently time-limited, how might a work of hoax horror whose time has passed speak to us now? To explore the afterlife of In the Dark, I discuss this foundational but little-studied work in the context of earlier scholarship on genres and modes that make use of illusions of authenticity, like creepypasta, found footage film, and alternate reality games (ARGs). I discuss how In the Dark functioned as a hoax when it was originally published in 2007, examining its amateur aesthetics, its interactions with viewers, and its inclusion of apparently meaningless material to create a sense of authenticity and implicate the reader in the storytelling process. Reflecting on how the last fifteen years have changed the way this hoax appears to and works on viewers, I suggest that as the immediate credibility of a horror hoax diminishes, a different kind of horror effect takes over, allowing the hoax to function in new, unintended ways. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Gothic Studies. 2023/03, Vol. 25, Issue 1, p42
- Document Type:Article
- Subject Area:Communication and Mass Media
- Publication Date:2023
- ISSN:1362-7937
- DOI:10.3366/gothic.2023.0152
- Accession Number:162253142
- Copyright Statement:Copyright of Gothic Studies is the property of Edinburgh University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.