An analytical framework to nowcast well-being using mobile phone data

An intriguing open question is whether measurements made on Big Data recording human activities can yield us high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we design a data-driven analytical framework that uses mobility measures and social measures extracted from mobile phone data to estimate indicators for socio-economic development and well-being. We discover that the diversity of mobility, defined in terms of entropy of the individual users' trajectories, exhibits (i) significant correlation with two different socio-economic indicators and (ii) the highest importance in predictive models built to predict the socio-economic indicators. Our analytical framework opens an interesting perspective to study human behavior through the lens of Big Data by means of new statistical indicators that quantify and possibly "nowcast" the well-being and the socio-economic development of a territory

La ciudad no es un árbol estático: comprender las áreas urbanas a través de la óptica de los datos de comportamiento en tiempo real

Cities are the main ground on which our society and culture develop today and will develop 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. Apart from measuring or monitoring such problems in a more comprehensive way, the analysis of those large datasets using modern machine learning techniques or causality detection permits to unveil of the behavioral roots behind them. As a result, only by incorporating real-time behavioral data can we design more efficient policies or interventions to improve such critical societal issues in our urban areas.Las ciudades son el principal terreno sobre el que se desarrollan —y se desarrollarán— nuestra sociedad y cultura. Frente a la concepción tradicional de las ciudades como espacio físico, en torno a nuestros barrios, el uso reciente de grandes conjuntos de datos de movilidad ha permitido estudiar el comportamiento humano a escalas espaciales y temporales sin precedentes, más allá de nuestros espacios residenciales. Este artículo muestra cómo es posible utilizar estos conjuntos de datos para investigar el papel que desempeña el comportamiento humano en problemas urbanos tradicionales como la segregación, la salud pública o las epidemias. Además de medir o monitorizar estos problemas de forma exhaustiva, el análisis de estos grandes conjuntos de datos mediante técnicas de aprendizaje automático o detección de causalidad permite desvelar raíces conductuales detrás de esos problemas. Como resultado, solo incorporando datos de comportamiento en tiempo real podemos diseñar políticas o intervenciones más eficientes que contribuyan a mejorar estos problemas sociales críticos en nuestras áreas urbanas

The Role of Gender in Social Network Organization

The digital traces we leave behind when engaging with the modern world offer an interesting lens through which we study behavioral patterns as expression of gender. Although gender differentiation has been observed in a number of settings, the majority of studies focus on a single data stream in isolation. Here we use a dataset of high resolution data collected using mobile phones, as well as detailed questionnaires, to study gender differences in a large cohort. We consider mobility behavior and individual personality traits among a group of more than $800$ university students. We also investigate interactions among them expressed via person-to-person contacts, interactions on online social networks, and telecommunication. Thus, we are able to study the differences between male and female behavior captured through a multitude of channels for a single cohort. We find that while the two genders are similar in a number of aspects, there are robust deviations that include multiple facets of social interactions, suggesting the existence of inherent behavioral differences. Finally, we quantify how aspects of an individual's characteristics and social behavior reveals their gender by posing it as a classification problem. We ask: How well can we distinguish between male and female study participants based on behavior alone? Which behavioral features are most predictive

End-user engagement in the design of communications services: lessons from the rural Congo

End-user engagement is considered essential when designing new sociotechnical systems, but in the context of designing large-scale infrastructural systems such as communications networks, this ideal is rarely put into practice. We examine the challenges of engaging end users in the design of communications services by exploring how communities from 15 villages in the rural Congo incorporate mobile phones into their daily lives. To analyze the changes in social and cultural capital that result from mobile phone use, we apply Bourdieu’s capital theory. This analysis exposes the difference in perceived value of the communication services between end users and the business owners of the infrastructure. The article concludes by suggesting new forms of partnership with end users to craft ways in which infrastructures and related organizations and practices can best cohere with local cultural views, specifics, beliefs, needs, or realities of concerned participants

Human-computer interaction for development (HCI4D):the Southern African landscape

Human-Computer interaction for development (HCI4D) research aims to maximise the usability of interfaces for interacting with technologies designed specifically for under-served, under-resourced, and under-represented populations. In this paper we provide a snapshot of the Southern African HCI4D research against the background of the global HCI4D research landscape.We commenced with a systematic literature review of HCI4D (2010-2017) then surveyed Southern African researchers working in the area. The contribution is to highlight the context- specific themes and challenges that emerged from our investigation