Investigation of Travel and Activity Patterns Using Location-based Social Network Data: A Case Study of Active Mobile Social Media Users

Yeran Sun,Ming Li

doi:10.3390/ijgi4031512

Abstract

Due to its relatively high availability and low cost, location-based social network (LBSN) (e.g., Foursquare) data (a popular type of volunteered geographic information) seem to be an alternative or complement to survey data in the study of travel behavior and activity analysis. Illustrating this situation, recently, a number of studies attempted to use LBSN data (e.g., Foursquare check-ins) to investigate patterns of human travel and activity. Of particular note is that compared to other individual-level characteristics of users, such as age, profession, education, income and so forth, gender is relatively highly available in the profiles of Foursquare users. Moreover, considering gender differences in travel and activity analysis is a popular research topic and is helpful in better understanding the changes in women’s roles in family, labor force participation, society and so forth. Therefore, this paper empirically investigates how gender influences the travel and activity patterns of active local Foursquare users in New York City. Empirical investigations of gender differences in travel and activity patterns are conducted at both the individual and aggregate level. The empirical results reveal that there are gender differences in the travel and activity patterns of active local users in New York City at both the individual and aggregate level. Finally, the results of the empirical study and the extent to which LBSN data can be exploited to produce travel diary data are discussed.

Highlights

Empirical investigations of travel and activity patterns exploit travel diary data collected from surveys
As a popular type of volunteered geographic information (VGI), georeferenced check-in data offered by location-based social networks (LBSNs) (Foursquare, Google Latitude, Facebook Places, etc.) create potential for analyzing human mobility [5,6]
Comparing land use characteristics of the areas covered by Low-High and by High-Low outliers suggests that (1) female users are more likely to visit commercial lands that are close to Central Business Districts (CBDs) or sub-CBD, whereas (2) male users are more likely to visit outdoor recreational lands that are distant from

Summary

Introduction

Empirical investigations of travel and activity patterns exploit travel diary data collected from surveys. Survey-based travel diary data is not highly available. Survey-based travel diary data is not open-access, or is open with a lack of detailed individual-level information on commuters (e.g., gender, age, etc.), and data collection based on household questionnaires is always a time-consuming task. As a popular type of volunteered geographic information (VGI), georeferenced check-in data offered by location-based social networks (LBSNs) (Foursquare, Google Latitude, Facebook Places, etc.) create potential for analyzing human mobility [5,6]. Profiles of LBSN users can offer individual-level characteristics (gender, age, etc.) of travelers It seems that LBSN data create potential for investigating the relationships between travel and activity patterns and individual-level characteristics

Objectives

Methods

Findings

Conclusion