At the beginning of this semester, I tweeted a poll. I wanted to know whether or not users would like to see me continue Oddly Specific Playlists, a DA I started up last year.
The results came back, and it seemed a revival was in order.
Oddly Specific Playlists is an interpersonal project to which users submit prompts & requests and gain curated personalised playlists. I receive these requests anonymously through a Google Form or via Twitter or Instagram. I then create the playlists, post them to Twitter and Instagram, and receive feedback. The model of this production process has been iterated many times during the life of this DA.
In essence, these playlists aim to affect their audience, and at the same time, do so through encouraging produsership. The playlists are framed through the users’ requests, and they rely on my schema or background knowledge that allows me to link songs I know to their request to affect the audience somehow. Mark Shevvy (2008) linked schema theory with music preference, saying, “understanding the similarities and differences in concepts associated with various genres may improve the efficiency with which music is used for communication.”
Originally, I developed this project as a source of comfort and entertainment for my music-loving classmates in lockdown. It was strongly inspired by Keana Wood’s TikTok account, The Unsent Project Instagram account, and Carly McNamara’s Anonymous Project. Of course, by the time this semester rolled around, we were out of lockdown, and a new social utility was in order. Research showed that the pandemic affected young people’s mental health immensely, so I thought a great new utility was creating playlists to help ease anxiety and depression. Users would submit their confessions, and I would make a playlist to help. However, this semester, users were less willing to disclose their personal feelings than last semester.
I run a risk by trying to sustain a project that is so dependant on the users, but in another way, it’s a plus because, due to its structure, it’s automatically extremely catered to the user’s needs. This means that when my user’s asked for playlists to inspire their fiction writing, I was happy to oblige.
This semester taught me that although it is useful to observe how your users use your content, predicting their behaviour and designing your project in tight parameters to suit is a failing model. Iterating your process and content to suit their requests and feedback will expand your user base, and in some cases, alter the social utility of your project. In the case of this semester and Oddly Specific Playlists, I started creating playlists that were being used for inspiration prompts for creative writing. While this was not the utility I had planned for, I embraced the opportunity and observed the playlists’ positive feedback.
I didn’t experiment very much with my production model last semester, however this semester I tested out several new kinds of playlists. I made some which followed the original format of request-playlist-Instagram, but I also posted some of my own playlists. I thought this was a good way of creating a relationship between myself and my users. I posted this semester’s playlists on my personal Spotify account, as opposed to the OSP account from last semester. In part, this helped intimacy between myself and my users, but it also helped me build a follower base in my own right, and of course, paying for one account is cheaper than two, addressing the “inexpensive” past of #FIST.
I ditched the graphic-creating that I did last year, and was able to test whether or not the extra effort was successful in growing users or not. The change in the aesthetic was well-received and took up less time than the full graphics I was making.
I also opened up a collaborative playlist and allowed my users to directly contribute to it’s creation. This broke my model as it removed me as the middle-man between my users, and they were able to put exacty what they wanted on the playlist.
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