How TikTok's FYP Algorithm Shapes Female Users' Content Preferences A Virtual Ethnographic Study in Bandung
DOI:
https://doi.org/10.31098/ijmadic.v4i2.2480Keywords:
Algorithmic Curation, Algorithmic Folk Theories, Content Preferences, TikTok FYP, Virtual Ethnography, Women UsersAbstract
TikTok's For You Page (FYP) is often described as if it directly determines what users prefer. This study instead examines preference formation as a recursive communication process between users and algorithmic curation. Using virtual ethnography, the study involved 20 women TikTok users in Bandung and combined online interviews, participatory platform observation, digital fieldnotes, and analysis of recurring content and interaction practices. The findings show that participants understood the FYP through practical folk theories: they expected likes, saves, shares, watch choices, and rapid skipping to teach the system what to display. These actions did not merely express pre-existing preferences; they also reorganized subsequent exposure and made some interests more salient. Four patterns were identified. First, participants experienced the FYP as a feedback loop rather than a one-way recommendation channel. Second, likes, saves, shares, and skipping were treated as stronger preference signals than following or commenting. Third, recommended content supported identity expression through fashion, beauty, everyday-life, educational, health, culinary, tourism, and entertainment content, with local relevance shaping interpretation. Fourth, longer use increased the perceived fit of recommendations but could also narrow variety, encouraging users to ignore or actively recalibrate unwanted content. The study contributes a communication-centered account of negotiated algorithmic curation: preference emerges through repeated exchanges among platform signals, user interpretations, identity work, and resistance.

