From Co-Location Patterns to an Informal Social Network of Gig Economy Workers
Image credit: CRiSS-LABAbstract
The labor market has transformed with the advent of the gig economy, characterized by short-term and fexible work arrangements facilitated by online platforms. As this trend becomes increasingly prevalent, it presents unique opportunities and challenges. In this manuscript, we comprehensively characterize the social networks of gig economy workers in each of the 15 cities studied. Our analysis reveals a scaling relationship between networks and the city population. In particular, we note the high level of modularity of the networks, and we argue that it results from the natural specialization of couriers along diferent areas of the cities. Furthermore, we show that degree and betweenness centrality is positively correlated with income but not with tenure. Our fndings shed new light on the social organization of the gig economy workers and provide valuable insights for the management and design of gig economy platforms.
Cristian Candia
Associate Professor, Data Science Institute, School of Engineering, Universidad del Desarrollo, Chile. Head of CRiSS-LAB.
Cristian Candia studies how societies transform information into collective relevance through attention, memory, preferences, and coordination. His work combines computational social science, network science, AI, and large-scale behavioral data to understand how groups, institutions, and societies decide what matters.
