GoogleTrendArchive: A Year-Long Archive of Real-Time Web Search Trends Worldwide

2026-03-23

AI Summary

This study addresses the limitation that Google Trending Now data is retained for only seven days, which hinders long-term research on global collective attention dynamics. To overcome this constraint, the authors present the first comprehensive archive of real-time trending data spanning 125 countries and 1,358 regions, compiled through automated collection and structured processing. The open-access dataset captures over 7.6 million fine-grained trending events, each annotated with multidimensional metadata—including identifiers, search volume ranges, timestamps, duration, geographic locations, and associated query clusters. By circumventing the platform’s seven-day access restriction, this resource enables inductive, keyword-free discovery of emerging trends and provides a foundational infrastructure for large-scale studies on information diffusion, cross-cultural attention patterns, and responses to突发 events at a global scale.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Knowledge Acquisition from the Web
• Humans and AI: Crowd Sourcing and Human Computation

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Responsible Web: Ethical and legal aspects of web-scale data analysis, uses and collection practices

Abstract

GoogleTrendArchive is a comprehensive archive of Google Trending Now data spanning over one year (from November 28, 2024 to January 3, 2026) across 125 countries and 1,358 locations. Unlike Google Trends, which requires specifying search terms in advance, Trending Now captures search queries experiencing real-time surges, offering a way to inductively discover trending patterns across regions for studying collective attention dynamics. However, Google does not provide historical access to this data beyond seven days. Our dataset addresses this gap by presenting an archive of Trending Now data. The dataset contains over 7.6 million trend episodes. Each record includes the trend identifier, search volume bucket, precise timestamps, duration, geographic location, and related query clusters. This dataset, among other, enables systematic studies of information diffusion patterns, cross-cultural attention dynamics, crisis responses, and the temporal evolution of collective information-seeking at a global scale. The comprehensive geographic coverage facilitates fine-grained cross-country or cross-regional comparative analyses.

Problem

• Google Trends
• Trending Now
• collective attention
• information diffusion
• historical data archive

Innovation

• Google Trending Now
• collective attention
• real-time search trends
• global archive
• information diffusion