Collaborative Research on the Algorithmic Differences between Netflix and Tik Tok
Hannah Matthy
The topic my partner and I decided to research was how different platforms use their algorithms in unique ways and how those strategies differ, specifically looking at Netflix and Tik Tok. My partner looked deeper into Netflixs algorithms and referenced the video we watched in class about how they tailor each user’s recommendations. Allaire discussed how Netflix uses different thumbnails for their videos to draw in users, taking a frame from the show that is similar to previous titles they had streamed. A huge similarity I saw early on when comparing the algorithm Netflix uses to Tik Tok was about watch time on the apps. An article that looked at Netflix algorithm and strategies explained that “…watch time is key. The algorithm tries to get people addicted rather than giving them what they really want” so that we use the platform more (Smith, 2021). Similar to them, Tik Tok prioritizes making sure people stay on the app for as long as possible, utilizing their own algorithm to curate videos on everyones ‘for you’ page. They look at previous data taken that includes what videos you have liked, saved, shared, and commented on and recommend similar videos. These videos are categorized into niches, as well as individual accounts. When there are matches in what niche a person interacts more with, they will then see more videos that fit that category. Niches can include shoppings, cooking, pets, family, and extremely specific as well. Tik Toks algorithm is very similar to Netflix in prioritizing time on the platform, and both have different strategies to achieve this for their company.
Collaborating on this topic was very easy to do because we were able to evenly divide our work and set expectations for what we expected the end result to be. Allaire and I each did our research on our own and made sure that we used the same concepts within our findings so that our video would flow easily. This was especially an easy collaboration because we had two topics that we were able to each do and put all of our dedication and time into our topics, and then comparing the similarities and differences we found. Creating the videos was done using two apps where we were able to read what we wanted to say while recording, avoiding missing any information and getting all of our ideas into words. Having two topics helped us record the videos separately and then add them together so there were no gaps instead of getting together to record. I did have a harder time putting the videos together than I expected, and wanted to find a platform that would add automated captions; I instead added key quotes from our videos in text bubbles to better highlight the important information. The deadline we were given was plenty of time to each gather information on our topics and organize our scripts, before then recording what we found and summarizing the key concepts of each platform. Creating our scripts first helped us stay organized while presenting, and allowed us to refer back to information from our partner in an easy way. I overall liked the layout of this project and its collaborative elements, and think it was very straightforward and helped us present our topic in an interesting way.
Our LEAP 5 Video: https://youtu.be/rwmUoffDZNY
References
Burk, D. (2020). Algorithmic Legal Metrics. AoIR Selected Papers of Internet Research. doi:10.5210/spir.v2020i0.11184
How the TikTok Algorithm Works in 2022 (and How to Work With It). (2022, February 12). Retrieved from https://blog.hootsuite.com/tiktok-algorithm/
Klug, D., Qin, Y., Evans, M., & Kaufman, G. (2021). Trick and Please. A Mixed-Method Study On User Assumptions About the TikTok Algorithm. 13th ACM Web Science Conference 2021. doi:10.1145/3447535.3462512
Smith, Ben. “How Tiktok Reads Your Mind.” The New York Times, The New York Times, 6 Dec.
2021, https://www.nytimes.com/2021/12/05/business/media/tiktok-algorithm.html?searchResultPosition=5.
