Correlating Pedestrian Flows and Search Engine Queries

TL;DR

This paper explores the correlation between urban pedestrian flows and Google search queries, demonstrating that search term frequencies can reflect location-specific pedestrian activity and help identify relevant content and advertisements.

Contribution

It introduces a novel method to correlate pedestrian flow data with search engine queries to characterize urban locations.

Findings

Pedestrian flows can be correlated with relevant search terms.

Search queries reflect location-specific urban activity.

The approach can identify relevant content and advertisements.

Abstract

An important challenge for ubiquitous computing is the development of techniques that can characterize a location vis-a-vis the richness and diversity of urban settings. In this paper we report our work on correlating urban pedestrian flows with Google search queries. Using longitudinal data we show pedestrian flows at particular locations can be correlated with the frequency of Google search terms that are semantically relevant to those locations. Our approach can identify relevant content, media, and advertisements for particular locations.