TL;DR: TikTok users interact with algorithm-curated versions of themselves, not their social network. Social media companies prioritising engagement through such algorithms create a self-mirroring experience that often overshadows meaningful social connections.
Who is this relevant for? Product teams, digital strategists, technology teams, AI teams, community managers, marketing & communication teams, policy teams—and anyone exploring algorithm-driven personalisation.
🎓 Researchers
Aparajita Bhandari, Cornell University
Sara Bimo, York University
📚 The Evidence
Research Objective: To examine how TikTok's algorithm influences user self-making and engagement compared to other platforms.
Sample: College students aged 18–24 from varied educational backgrounds, including computer science, communication, and engineering. User interviews with 14 participants who used TikTok for at least 30 minutes daily over a month.
Methodology: The study combined a walkthrough analysis of TikTok’s interface and features with semi-structured interviews. Researchers used grounded theory to identify themes related to algorithm awareness, content consumption, and self-creation across platforms.
Citation:
Bhandari, A., & Bimo, S. (2022). Why’s Everyone on TikTok Now? The algorithmized self and the future of self-making on social media. Social Media + Society, 8(1), 1–11.
Access the full paper - https://doi.org/10.1177/20563051221086241
📊 Key Results
Awareness of the Algorithm: Participants exhibited a heightened awareness of TikTok's "For You" algorithm, often describing it as "getting to know" their preferences with striking accuracy.
Content Over Connections: Users engaged more with curated content tailored to their interests rather than content from their social networks, reducing traditional social interactions.
Algorithmic Personalisation Shapes Experience: The algorithm’s dominance created a feedback loop, where users felt increasingly understood but also constrained by the curated scope of their feed.
Never before in history have 50 designers made decisions that would have an impact on two billion people
👉🏾 Vishal’s Evidence-Based Strategy
1️⃣ Encourage Discovery: Design algorithms to present diverse content, helping users explore different perspectives.
2️⃣ Support Community: Create features to enable meaningful human interactions and strengthen community ties.
3️⃣ Be Transparent: Explain how algorithms work and provide tools for users to adjust their experience.
🧪 Footnote
Evidence evolves over time and will NOT work across all contexts—start with a small experiment to find out what works for your specific challenge and audience.
P.S. I offer limited spots each year for our online masterclass, which includes two personalised 90-minute training sessions to help you apply our behavioural science tools.