Selected Papers of #AoIR202 3 : The 24th Annual Conference of the Association of Internet Researchers Philadelphia, PA, USA / 18-21 Oct 2023 Rouse, L. and M. Stanf ill. (2023, October). Mapping Tumblr Through Fannish Homophilies . Paper presented at AoIR2023: The 24th Annual Conference of the Association of Internet Researchers. Philadelphia, PA, USA: AoIR. Retrieved f rom http://spir.aoir.org. MAPPING TUMBLR THROUGH FANNISH HOMOPHILIES Lauren Rouse University of Central Florida Mel Stanfill University of Central Florida Tumblr, a microblogging platform that was founded in 2007, hosts various communities organized around interests. The platform has had a varied history, changing ownership multiple times over its lifespan. In 2019, there were nearly 475 million individual blogs across the site, with 376 million unique visitors worldwide (a number that had decreased after Tumblr banned adult content in 2018)(Rouse and Salter 2021); as Tiidenberg, Hendry, and Abidin note, “tumblr has consistently had more active users than Twitter, Snapchat, Baidu, or LinkedIn” (2016, 2) Combining many of the most the popular aspects of social media and blogging platforms, Tumblr allows users to curate their blog, or profile, aggregating content reflecting interests spanning sports, music, literature, or art. Users can post a variety of content including videos, music files, images, chat posts, or links. They can also reblog other users’ content, which functions similarly to retweeting by reposting given content to their own followers. Other features include liking, commenting, and tagging. The experience of Tumblr is organized around the “dashboard,” which—rare among contemporary social media platforms—is a reverse chronological feed of the blogs a user follows. Users can also discover content through tracking particular tags or an algorithmic “For you” tab. However, as the common joke on the platform about a post “breaking containment” shows, generally content circulates within smaller groups rather than across the entire site; Tiidenberg, Hendry, and Abidin describe the platform as “experienced through silos” that are “sustained through shared practices, vernacular, and sensibility” (2016, 13) Tumblr is also notoriously difficult to study. The site is notably hard to navigate (Hillman, Procyk, and Neustaedter 2014). It is also ephemeral, in the sense that “most content posted to the site quickly becomes irrecoverable” (Popova 2020, 81) As Proferes and Morrissey note, while the reblogging function allows for users to add their own comments or hashtags to a post, posts “tend to fragment into multiple branches,” such that “reconstructing an entire conversation is difficult” (2020, 32). This differs from a function like replies on Twitter or Facebook that are threaded. Additionally, as Louisa Ellen Stein describes, “although tags are intended to help with categorizing, archiving, http://spir.aoir.org/ and retrieval, Tumblr users often include tags to capture their momentary response to an image, to theorize or extrapolate, or to inscribe the imagined audience into the post” (2015, 158). As a result of this usage norm, tags are rarely useful as metadata for post discovery or retrieval. Attu and Terras note (2017) that “the majority of papers published have a conceptual focus: explaining how Tumblr works when positioned within a specific field of interest, closely followed by message-based works which study Tumblr content” (3). However, they also note that user studies have become more popular, as researchers attempt to understand the various motivations for choosing this particular pattern over other social media platforms like Twitter or Facebook (Bury et al. 2013; Hillman, Procyk, and Neustaedter 2014). Some researchers use content analysis as a way of determining how identities and representation plays into the distribution of media across the site (Chang et al. 2014; Xu et al. 2014; Dame 2016; Bourlai 2017; Wick and Harriger 2018). Others use close reading and interviews with users of the site to investigate often-toxic behaviors that permeate many interactions within various communities, including gatekeeping, bullying, and systemic oppression (Cavazos-Rehg et al. 2017; Ringrose and Lawrence 2018; Byron 2019; Keller 2019). However, there is a lack of research on the network of users and information flow on Tumblr. Because so much of the platform and its communities are sequestered around tags or specific accounts, and accounts do not have to follow others in order to access the content a specific blog might post, it is difficult to understand how users, and specifically for our purposes here fans, navigate throughout the platform. Using survey data from a 2022 survey of fans that was distributed on Tumblr between February 22 and March 21, 2022, this paper speculatively maps the network of Tumblr. Tumblr is home to fandoms of all kinds, acting as a space where fans can gather, discuss theories, produce fan texts and media, and interact with fanworks, making them one of the key distinctive communities that use the site and a suitable community to investigate the shape of the network. In analyzing the 5,000 responses from our survey, we began to notice distinct patterns where the responses seemed to echo one another as various demographic answers would be the same in a clump. One pocket of similar responses was from our question on disability. In the survey, we asked for participants to self-describe any disabilities that they have. We received 65 responses to this question which listed Ehlers-Danlos Syndrome, a group of inherited disorders which affects connective tissue in the body. In the United States, the Mayo Clinic classifies it as a rare disorder, and within the worldwide population, EDS affects just 1 in every 5,000 people (“Ehlers-Danlos Syndrome” n.d.; “Ehlers-Danlos Syndrome” n.d.). People with this condition are thus very overrepresented in our data, and furthermore these responses all were reported around the same time, suggesting that the post with the survey was being reblogged through a section of the network with a high degree of homophily around that identity. Beginning from this example, we take a twofold approach. First, we analyze the prevalence of particular demographic answers over time to find points at which a large number of responses have similar identities. Second, we use the baseline probability of any given answer within our data set to examine times when it becomes disproportionately prevalent compared to elsewhere in the data. Through looking at these correlations between time and probability in specific demographic answers, we can identify moments when the survey was traveling through a homophilic network within the platform, and therefore extract information about how homophily works on this platform. By mapping Tumblr through these survey homophiles, we can gain a greater understanding of how people gather and interact on the platform. This has implications both for questions of community and subcultural belonging, but also issues like the spread of mis- and disinformation. References Attu, Rose, and Melissa Terras. 2017. “What People Study When They Study Tumblr: Classifying Tumblr-Related Academic Research.” Journal of Documentation 73 (3): 528–54. https://doi.org/10.1108/JD-08-2016-0101. Bourlai, Elli. 2017. “‘Comments in Tags, Please!’: Tagging Practices on Tumblr.” Discourse, Context & Media 22 (October). https://doi.org/10.1016/j.dcm.2017.08.003. 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