#Mobile phone data #influence #adoption #marketing

Long-Range Social Influence in Phone Communication Networks on Offline Adoption Decisions

Authors: Yan Leng , Xiaowen Dong, Esteban Moro, Alex Pentland Publication: Information Systems Research, Articles in Advance 21 Jun (2023) LINK Abstract: We use high-resolution mobile phone data with geolocation information and pro- pose a novel technical framework to study how social influence propagates within a phone communication network and affects the offline decision to attend a performance event. Our fine-grained data are based on the universe of phone calls made in a European country between January and July 2016. ...

#Mobility #Data Science #machine learning #latent

Identifying latent activity behaviors and lifestyles using mobility data to describe urban dynamics

Authors: Yanni Yang, Alex Pentland, Esteban Moro Publication: EPJ Data Science 12, Article number: 15 (2023) LINK Abstract: Urbanization and its problems require an in-depth and comprehensive understanding of urban dynamics, especially the complex and diversified lifestyles in modern cities. Digitally acquired data can accurately capture complex human activity, but it lacks the interpretability of demographic data. In this paper, we study a privacy-enhanced dataset of the mobility visitation patterns of 1. ...

#2023 #covid19 #Mobile phone data #Mobility #inequality

Behavioral changes during the COVID-19 pandemic decreased income diversity of urban encounters

Authors: Takahiro Yabe, Bernardo García Bulle Bueno, Xiaowen Dong, Alex Pentland & Esteban Moro Publication: Nature Communications volume 14, Article number: 2310 (2023) LINK Abstract: Diversity of physical encounters in urban environments is known to spur economic productivity while also fostering social capital. However, mobility restrictions during the pandemic have forced people to reduce urban encounters, raising questions about the social implications of behavioral changes. In this paper, we study how individual income diversity of urban encounters changed during the pandemic, using a large-scale, privacy-enhanced mobility dataset of more than one million anonymized mobile phone users in Boston, Dallas, Los Angeles, and Seattle, across three years spanning before and during the pandemic. ...

#segregation #Urban Science #Mobile phone data #crime

Diversity beyond density: Experienced social mixing of urban streets

Authors: Zhuangyuan Fan, Tianyu Su, Maoran Sun, Ariel Noyman, Fan Zhang, Alex ‘Sandy’ Pentland, Esteban Moro Publication: PNAS Nexus, Volumen 2, Issue 4, pgad077, 2023 LINK Abstract: Urban density, in the form of residents’ and visitors’ concentration, is long considered to foster diverse exchanges of interpersonal knowledge and skills, which are intrinsic to sustainable human settlements. However, with current urban studies primarily devoted to city- and district-level analyses, we cannot unveil the elemental connection between urban density and diversity. ...

#Mobile phone data #Segregation #food #machine learning

A city is not a static tree: understanding urban areas through the lens of real-time behavioral data

Authors:Esteban Moro Publication: ZARCH, 19, 28–39. 2023 LINK Abstract: Cities are the main ground on which our society and culture develop today and will evolve in the future. Against the traditional understanding of cities as physical spaces mostly around our neighborhoods, recent use of large-scale mobility datasets has enabled the study of our behavior at unprecedented spatial and temporal scales, much beyond our static residential spaces. Here we show how it is possible to use these datasets to investigate the role that human behavior plays in traditional urban problems like segregation, public health, or epidemics. ...

#epidemics #social media #Data Science #Sensors #Complex Networks

Social Media Sensors to Detect Early Warnings of Influenza at Scale

Authors: David Martín-Corral, Manuel García-Herranz, Manuel Cebrian, Esteban Moro Publication: medRxiv 2022.11.15.22282355 LINK Abstract: Detecting early signs of an outbreak in a viral process is challenging due to its exponential nature, yet crucial given the benefits to public health it can provide. If available, the network structure where infection happens can provide rich information about the very early stages of viral outbreaks. For example, more central nodes have been used as social network sensors in biological or informational diffusion processes to detect early contagious outbreaks. ...