Computer Science
Chat with the ’For You’ Algorithm: An LLM-Enhanced Chatbot for Controlling Video Recommendation Flow
Document Type
Conference Paper
Abstract
The rise of short-form video platforms like TikTok, driven by algorithmic recommendations, fosters immersive flow experiences. While users value personalization and engagement, they also seek greater agency over their For You recommendations. This paper designs, prototypes, and evaluates TKGPT, an LLM-enhanced conversational interface that helps users articulate their interests and understand recommendations. Through qualitative interviews and a user study, we examine how the TKGPT influences algorithmic folk theories and the sense of agency. Findings show that users primarily use TKGPT to seek relevant videos, explain preferences, and exert control over the algorithm. The resulting For You videos better reflect user interests, enhance the understanding of algorithm, improve content relevance, and reduce feelings of exploitation. Notably, users’ sense of agency is significantly associated with their improved understanding of how the algorithm works. We discuss the opportunities and challenges of using conversational user interfaces to enhance user control over video recommendations. © 2025 Copyright held by the owner/author(s).
Publication Title
CUI 2025 - Proceedings of the 2025 ACM Conference on Conversational User Interfaces
Publication Date
7-2025
ISBN
9798400715273
DOI
10.1145/3719160.3736628
Keywords
chatbot, folk theory, Generative AI, large-language model, recommendation algorithm, TikTok, video
Repository Citation
Niu, Shuo; Vishnuvardhan, Dikshith; and Punnam, Venkata Sai Reddy, "Chat with the ’For You’ Algorithm: An LLM-Enhanced Chatbot for Controlling Video Recommendation Flow" (2025). Computer Science. 242.
https://commons.clarku.edu/faculty_computer_sciences/242
APA Citation
Niu, S., Vishnuvardhan, D., & Punnam, V. S. R. (2025, July). Chat with the ‘For You’Algorithm: An LLM-Enhanced Chatbot for Controlling Video Recommendation Flow. In Proceedings of the 7th ACM Conference on Conversational User Interfaces (pp. 1-16).
Cross Post Location
Student Publications
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
