| Title | Mirror of Your Mind |
|---|---|
| Contributor | Isabel Munson (author) |
| DOI | https://doi.org/10.32376/3f8575cb.23170ae3 |
| Landing page | https://www.mediastudies.press/pub/munson-mirror/ |
| Publisher | mediastudies.press |
| Published on | 2021-07-15 |
| Short abstract | GAZING INTO TIKTOK’S For You Page—an algorithmically curated, personalized feed that shows videos the platform thinks you will like, learning over time what kind of content will increase your engagement—can be like looking into a hall of mirrors |
| Long abstract | GAZING INTO TIKTOK’S For You Page—an algorithmically curated, personalized feed that shows videos the platform thinks you will like, learning over time what kind of content will increase your engagement—can be like looking into a hall of mirrors. It’s hard to know if its at times uncanny accuracy stems from superior analytics and data harvesting (which are widely mythologized and which companies are often incentivized to oversell) or from the fact that most users can be guided to generally predictable categories. On TikTok, comments like “so we’re really all living the same life huh?” are not uncommon. There may also be an availability bias to those occasions when the algorithm guesses really, really right: We remember those, while forgetting the videos that didn’t click. Sometimes the For You Page algorithm is extremely literal, clumsy, and obvious in its techniques: Watch a video of a girl who happens to be a hijabi; be presented with three more hijabis the next day. Despite this, the algorithm can begin to seem to know users better than they know themselves. Its occasional clumsiness and errors in taste may lower users’ defenses, creating a randomness that may offset the creepiness of being accurately pigeonholed. |