Alone Together - Convergence Culture and the Slender Man Phenomenon
Bibliographic record
Abstract
This project engages in a close examination of the Slender Man phenomenon, an online practice in which a community of pseudonymous enthusiasts share scary stories featuring a faceless, long-limbed, humanoid monster in a black business suit. The stories take various forms, including text-based narrative, amateur video, doctored images, and games. They are presented with an affectation of folklore, and treat the accounts as true testimonies of encounters they, or others they know, have allegedly had with Slender Man. This is a self-conscious effort on the part of its creators to manifest Slender Man as a real-life legend. Resulting from this effort, several individuals have carried out acts of real-world violence in the name of Slender Man, or with some connection to him. In response to these acts, and the ensuing moral panic, members of the community defensively stated that it was the responsibility of their readers to be able to know the difference between fantasy and reality. Yet, as this dissertation demonstrates, the Slender Man phenomenon itself is predicated on using digital media to blur this distinction. \nThrough readings of Slender Man in various media forms, this dissertation shows how it blends horror aesthetics with the online cultures of trolling—in which individuals intentionally misrepresent themselves in order to mislead and antagonize others, allegedly for the lulz—that is, for the laughs, pranking or joking. Trolling has however produced many serious consequences, from individuals targeted for harassment to bad-faith political movements that disrupt existing institutional functions more broadly. In its origins, trolling began as apocryphal storytelling designed to mislead others into believing they were true and expose the ignorance of newbies. Notably, the sites in which this occurred evolved to become the fora from which the similarly apocryphal stories in the Slender Man text community originate, such as 4Chan. These same pseudonymous fora have acted as safe havens for bad actors that have gone on to become notorious for their promotion of real-world violence, from Erik Minassian’s violence in the name of the incel community to Elliot Rodger’s misogynistic manifesto posed to 4Chan. \nIn short, this dissertation argues that Slender Man texts act as a canary in a coal mine, and that the mechanics of online horror communities lay bare the underlying strategies of trolling or post-truth internet culture more broadly. I undertake a close aesthetic and ideological examination of Slender Man in image, text, video and game, to offer a portrait of the community that shares them. The stories offer a glimpse into the anxieties, tensions, and alienation experienced in life online as a result of hypermediacy, premediacy, and anonymity. While much has been written regarding the potential for collaboration online and the possibilities for grassroots organization and community-building, the positive ends this convergence culture offers are offset to some extent by the kinds of anxieties emerging from a disaffected and alienated community. Ultimately, this project offers an account of the evolving relationship between interactive fiction, trolling, and political disaffection, a media ecology that is becoming ever more urgent to understand in twenty-first century society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".