Final Post, here we go!
Over the course of going through the internet, looking for different materials for my blog stream I influenced my data algorithm to give me content that related to our classwork. When I first approached a new block I would search for content that might give me a brief overview of what we were studying. Youtube videos on sci-fi and community, TedTalks about algorithms, or Pinterest posts about cyberculture. What is notable about my blog and this algorithm is that I also found meaning in humor. I enjoyed posting a lot of videos that I thought were both amusing but related to our course topics in a new way. Videos about the authenticity of bloggers, about algorithms writing skits, or people struggling with different technology.
Block 1: Cyberculture
This block was a great way to launch the class. I was feeling very overwhelmed this first week with setting everything up, trying to get organized and make sure that I was doing everything “right”. The film festival was a really cool way to see all these different pieces of cyberculture. I’m really into science-fiction so I found the block to build on my interests. At this point there hadn’t been much of a response from my algorithms on my social media or the internet because the first block was in line with an interest that I already had.
Block 2: Community Cultures
After reading the literature and from experience in my own online communities I know how valuable an online community can be. “Recent developments in ethnographic online research reveal how much online communities are changing notions of the self, systems of social support, personal and work relationships, institutional power, and social activism.” (Kozinets, 2009. pg 40). This reflected my experience with my fandom community but not of my MOOC. Despite my MOOC having a very similar pattern to my online fandom community, the authenticity of the two communities was vast. While the participants of the MOOC are encouraged to interact, to like the Facebook page and follow the class on Twitter, but few do. MOOCs seem to be mostly isolating. “Research has highlighted passive behaviors in MOOC participants, and questions have been raised about the isolation of students in such open educational formats.” (Bayne et al. 2019). When you’re in an environment, a community and you feel that you have no impact that matters, then you don’t seek to make an impact.
For my algorithm in this block, I sought to feel less isolated. I actually interacted with my fandom community more because it related to my MOOC (The Rise of Superheroes and Their Impact on Pop Culture). I found myself almost seeking companionship from both this community and my algorithm. I searched for extra information for class and spent time reading more fandom than normal.
Block 3: Algorithmic Culture
Block 3 became very intense in the middle with Covid 19 kicking into high gear. This greatly influenced my algorithm both in the play activity and in my regular searching. What I found absolutely fascinating was the way my algorithm responded to these searches of Covid 19, particularly in Pinterest where my play happened. I got feedback that promoted calm, I saw advertisements for apps called “Calm” and “Breath.” On Pinterest, I got recommended “coping strategies”, “relaxation yoga”, and “the importance of destressing.” This made me wonder, to what capacity are algorithms designed to take care of us?
I’ve been reflecting on how these algorithms, these searches, and all this collective data represent me. How does it show what I value, my thinking process and how I relate to the course material? Who does my artifacts think I am?
I heavily used Youtube and Twitter. I chose Twitter because I enjoy communicating with others in the class and feeling connected, also because it was easy to post other materials there as well, such as Pinterest posts, TedTalks and other articles. I chose Youtube because I found a lot of information there, and with the algorithm, the more material I looked at, the more I got in return. This class made me reflect on the ideas of what I am feeding to the algorithm and what the algorithm, in turn, is giving me. Where do we begin and the algorithms end? And does this question even matter?
Bayne, S., Evans, P., Ewins, R., Knox, J., Lamb, J., Macleod, H., O’Shea, C., Ross, J., Sheail, P., Sinclair, C. (2019 DRAFT). The Manifesto for Teaching Online.
Kozinets, R.V. (2010) Chapter 2 ‘Understading Culture Online’, Netnography: doing ethnographic research online. London: Sage. Pp. 21-40.