# LLM-Enhanced Topical Trend Detection at Snapchat

Source: [LLM-Enhanced Topical Trend Detection at Snapchat](<https://www.sota2.com/research/paper/69f4338e55a3c32af89fd12c>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-05-02T05:00:04.163Z

Authors: Hangqi Zhao, Jay Li, Abhiruchi Bhattacharya, Cong Ni, Jason Yeung, Jinchao Ye, Kai Yang, Akshat Malu, Manish Malik

Published: 2026-04-29T19:32:42.000Z

## Abstract

Automatic detection of topical trends at scale is both challenging and essential for maintaining a dynamic content ecosystem on social media platforms. In this work, we present a large-scale system for identifying emerging topical trends on Snapchat, one of the world's largest short-video social platforms. Our system integrates multimodal topic extraction, time-series burst detection, and LLM-based consolidation and enrichment to enable accurate and timely trend discovery. To the best of our knowledge, this is the first published end-to-end system for topical trend detection on short-video platforms at production scale. Continuous offline human evaluation over six months demonstrates high precision in identifying meaningful trends. The system has been deployed in production at global scale and applied to downstream surfaces including content ranking and search, driving measurable improvements in content freshness and user experience.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Content Ranking on Snapchat Online A/B Testing (July-Dec 2025 Production Data)](<https://www.sota2.com/research/sota/content-ranking-on-snapchat-online-a-b-testing-july-dec-2025-production-data.md>): Content Ranking; Snapchat Online A/B Testing July to December 2025 (Production); Spotlight Story View Lift (US): 0.86.

- [Content Search on Snapchat Online A/B Testing July to December 2025 (Online Production)](<https://www.sota2.com/research/sota/content-search-on-snapchat-online-a-b-testing-july-to-december-2025-online-production.md>): Content Search; Snapchat Online A/B Testing July to December 2025 (Online Production); Impression Timeliness (\<3 days): 2.38.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2604.27131>)

[PDF](<https://arxiv.org/pdf/2604.27131.pdf>)