Published in EPJ Data Science
Linked social media and survey data have the potential to be a unique source of information for social research. While the potential usefulness of this methodology is widely acknowledged, very few studies have explored methodological aspects of such linkage. Respondents produce planned amounts of survey data, but highly variant amounts of social me...
Published in EPJ Data Science
We present a study of the evolution of the political landscape during the 2015 and 2019 presidential elections in Argentina, based on data obtained from the micro-blogging platform Twitter. We build a semantic network based on the hashtags used by all the users following at least one of the main candidates. With this network we can detect the topic...
Published in EPJ Data Science
We study the problem of modeling temporal networks constrained by the size of a concurrent set, a characteristic of temporal networks shown to be important in many application areas, e.g., in transportation, social, process, and other networks. We propose a competition-driven model for the generation of such constrained networks. Our method carries...
Published in EPJ Data Science
Inferring mobile phone users’ home location, i.e., assigning a location in space to a user based on data generated by the mobile phone network, is a central task in leveraging mobile phone data to study social and urban phenomena. Despite its widespread use, home detection relies on assumptions that are difficult to check without ground truth, i.e....
Published in EPJ Data Science
Urban green space is thought to contribute to citizen happiness by promoting physical and mental health. Nevertheless, how urban green space and happiness are related across many countries with different socioeconomic conditions has not been explored. By measuring the urban green space score (UGS) from high-resolution satellite imagery of 90 global...
Published in EPJ Data Science
Multiple driving forces shape cities. These forces include the costs of transporting goods and people, the types of predominant local industries, and the policies that govern urban planning. Here, we examine how agglomeration and dispersion change with increasing population and population density. We study the patterns in the evolution of urban for...
Published in EPJ Data Science
Many studies have shown that there are regularities in the way human beings make decisions. However, our ability to obtain models that capture such regularities and can accurately predict unobserved decisions is still limited. We tackle this problem in the context of individuals who are given information relative to the evolution of market prices a...
Published in EPJ Data Science
The establishment of new collaborations among scientists fertilizes the scientific environment, fostering novel discoveries. Understanding the dynamics driving the development of scientific collaborations is thus crucial to characterize the structure and evolution of science. In this work, we leverage the information included in publication records...
Published in EPJ Data Science
In recent years there has been a growing interest in analyzing human behavioral data generated by new technologies. One type of digital footprint that is universal across the world, but that has received relatively little attention to date, is spending behavior. In this paper, using the transaction records of 1306 bank customers, we investigated th...
Published in EPJ Data Science
To monitor risk in temporal financial networks, we need to understand how individual behaviours affect the global evolution of networks. Here we define a structural importance metric—which we denote as le\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage...
