Transformative Works and Cultures releases No. 24

Transformative Works and Cultures has released No. 24, a special issue on Queer Female Fandom, guest edited by Julie Levin Russo and Eve Ng.

The essays in this issue focus on queer women as the object of fan study. Texts analyzed include Rizzoli & Isles, Grey’s Anatomy, The L Word, Wynonna Earp, The 100, Orphan Black, and Once Upon a Time. In addition, authors discuss J-pop and K-pop musicians and independent Web series. A multimedia piece by editor Russo provides examples of queer female fan vids.

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OTW Guest Post

OTW Guest Post: Ann McClellan

From time to time, the OTW will be hosting guest posts on our OTW News accounts. These guests will be providing an outside perspective on the OTW or aspects of fandom where our projects may have a presence. The posts express each author’s personal views and do not necessarily reflect the views of the OTW or constitute OTW policy. We welcome suggestions from fans for future guest posts, which can be left as a comment here or by contacting us directly.

Ann McClellan is Professor and Chair of English at Plymouth State University where she teaches classes on 19th and 20th century British Literature, film/adaptation studies, and digital literature. Her scholarship interests include Sherlock Holmes and/in popular culture and British women’s campus fiction. Today, Ann talks about her article on Sherlock Holmes fandom in the latest issue of Transformative Works and Cultures.

How did you first become aware of fandom and fanworks?

In a sense, I always ‘knew’ about fandom through my own research and teaching interests in adaptation studies, but no one ever called such texts “fan texts” when I was in school. I’ve long been interested in how ‘authorized’ writers and filmmakers have colonized and transformed canonical texts like The Scarlet Letter, Jane Austen’s novels, and Shakespeare’s plays, but it wasn’t until a friend introduced me to Sherlock when it premiered on PBS in 2010 that I really learned about fan culture and fandom more specifically.

Of course, events like ComicCon had already entered the contemporary zeitgeist by 2010 when Sherlock reached the US, so I was aware of such gatherings, but I had no idea how pervasive and diverse they were until my own explorations in online Sherlock fandom beginning in 2011. I can’t remember the precise reason or prompt, but I began researching Sherlock online and discovered LiveJournal and fan fiction for the first time—in my forties! I instantly became addicted to the serial nature of fan fiction and writers’ ability to immerse me into the show’s world through various ‘fix it’ fics, AU fantasies, slash, and other genres. Soon, this new world of fan fiction became my personal and professional obsession and my previous plan to write a book on Sherlock Holmes in popular culture quickly morphed into a book on Sherlock fan fiction and world building.

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OTW Guest Post

OTW Guest Post: Smitha Milli

From time to time, the OTW will be hosting guest posts on our OTW News accounts. These guests will be providing an outside perspective on the OTW or aspects of fandom where our projects may have a presence. The posts express each author’s personal views and do not necessarily reflect the views of the OTW or constitute OTW policy. We welcome suggestions from fans for future guest posts, which can be left as a comment here or by contacting us directly.

Smitha Milli is a 4th-year undergraduate at UC Berkeley whose research interests lie in artificial intelligence and cognitive science. Today, Smitha talks about her research using natural language processing to reveal patterns in fanfiction texts, the results of which is available online.

How did you come to work with fanfiction in your research?

At the time I started this project my main research focus was in natural language processing (NLP). Natural language processing is a subfield of artificial intelligence that is concerned with creating algorithms to process and understand language. If you’ve ever used Google Translate or Siri, you’ve used products that depend on NLP research!

In addition to having many commercial applications, NLP can also be used as a tool to explore literature. People have automatically tracked dynamic relationships between characters, created computational models of literary character, and analyzed the change in emotional content over the course of a story. However, a bottleneck to improving algorithms in the literary domain was the lack of a large-scale dataset of modern literature. I originally started looking into fanfiction as a source for this kind of data. As I looked further, I found that the structure of fanfiction also made it possible to define interesting, new problems for NLP and I became interested in computationally analyzing social science questions about fanfiction.

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