[Paper Review] Human Mobility during COVID-19 in the Context of Mild Social Distancing: Implications for Technological Interventions

Myeong Lee, Seongkyu Lee+2 more|arXiv (Cornell University)|Jun 28, 2020

Human Mobility and Location-Based Analysis35 references4 citations

TL;DR

This study analyzes human mobility in a major South Korean city during the early COVID-19 pandemic under mild social distancing, using anonymized smartphone data from over 1 million users. It identifies five distinct mobility typologies based on behavioral patterns, revealing significant shifts in daily routines and social interactions, and provides design implications for equitable technological interventions in future pandemics.

ABSTRACT

The COVID-19 pandemic has brought both tangible and intangible damage to our society. Many researchers studied about its societal impacts in the countries that had implemented strong social distancing measures such as stay-at-home orders. Among them, human mobility has been studied extensively due to its importance in flattening the curve. However, mobility has not been actively studied in the context of mild social distancing. Insufficient understanding of human mobility in diverse contexts might provide limited implications for any technological interventions to alleviate the situation. To this end, we collected a dataset consisting of more than 1M daily smart device users in the third-largest city of South Korea, which has implemented mild social distancing policies. We analyze how COVID-19 shaped human mobility in the city from geographical, socio-economic, and socio-political perspectives. We also examine mobility changes for points of interest and special occasions such as transportation stations and the case of legislative elections. We identify a typology of populations through these analyses as a means to provide design implications for technological interventions. This paper contributes to social sciences through in-depth analyses of human mobility and to the CSCW community with new design challenges and potential implications.

Motivation & Objective

• To understand how human mobility changed during the early COVID-19 pandemic in a city with mild social distancing, not strict lockdowns.
• To examine mobility patterns across different geographical, socio-economic, and socio-political contexts during the pandemic.
• To identify distinct mobility typologies based on behavioral patterns, especially regarding essential activities and social interactions.
• To provide actionable design implications for technological interventions that support public health while minimizing social inequities.
• To contribute to crisis informatics and CSCW by grounding technological design in real-world mobility dynamics during a pandemic.

Proposed method

• Collected anonymized mobility data from over 1 million smartphone users in the third-largest city in South Korea from December 2019 to May 2020.
• Used Voronoi tessellation to spatially aggregate mobility data, ensuring coverage even in low-traffic areas.
• Classified points of interest (POIs) into land-use categories, using the highest-ranking manually-coded type for each location.
• Analyzed temporal patterns of mobility across different times of day and days of the week, including holidays and special events.
• Identified mobility typologies through cluster analysis of daily movement patterns, focusing on work, shopping, and socializing behaviors.
• Used housing transaction data as a proxy for socio-economic status, acknowledging its limitations and potential biases.

Experimental results

Research questions

• RQ1 How did human mobility patterns shift during the early COVID-19 pandemic in a city with mild social distancing compared to pre-pandemic levels?
• RQ2 What are the differences in mobility behaviors across socio-economic, geographical, and socio-political groups during the pandemic?
• RQ3 How did mobility change for specific points of interest such as transportation hubs and recreational sites during the pandemic?
• RQ4 What are the distinct behavioral typologies of mobility groups, and what do they reveal about people’s pandemic responses?
• RQ5 What design implications can be derived for technological interventions that support public health while addressing social equity?

Key findings

• Mobility decreased significantly during the pandemic, especially in the afternoons and evenings on holidays, indicating a sharp decline in socializing and leisure activities.
• The peak in mobility at bus stations during morning and dinner times on holidays disappeared in the PANIC period, suggesting reduced domestic travel and outdoor recreation.
• A typology of five distinct mobility groups was identified, including essential workers, crowd-avoiding outdoor workers, and individuals with reduced social mobility.
• People’s socializing and family interactions, especially during dinner hours on holidays, were markedly reduced, signaling a shift in daily routines and potential mental health impacts.
• The study found that mobility patterns were highly sensitive to socio-economic and cultural factors, with disparities in behavior across different demographic groups.
• Despite limitations in data resolution and proxy measures, the analysis revealed consistent and meaningful shifts in mobility that align with public health trends and behavioral changes.