scholarly journals Mobile Phone Indicators and Their Relation to the Socioeconomic Organisation of Cities

2019 ◽  
Vol 8 (1) ◽  
pp. 19 ◽  
Author(s):  
Clémentine Cottineau ◽  
Maarten Vanhoof
Keyword(s):  
Mobile Phone ◽  
Census Data ◽  
Social Science Research ◽  
Science Research ◽  
Computational Social Science ◽  
Mobile Phone Data ◽  
Spatial And Temporal Heterogeneity ◽  
Statistical Relationships ◽  
Socioeconomic Data ◽  
The City

Thanks to the use of geolocated big data in computational social science research, the spatial and temporal heterogeneity of human activities is increasingly being revealed. Paired with smaller and more traditional data, this opens new ways of understanding how people act and move, and how these movements crystallise into the structural patterns observed by censuses. In this article we explore the convergence between mobile phone data and more traditional socioeconomic data from the national census in French cities. We extract mobile phone indicators from six months worth of Call Detail Records (CDR) data, while census and administrative data are used to characterize the socioeconomic organisation of French cities. We address various definitions of cities and investigate how they impact the statistical relationships between mobile phone indicators, such as the number of calls or the entropy of visited cell towers, and measures of economic organisation based on census data, such as the level of deprivation, inequality and segregation. Our findings show that some mobile phone indicators relate significantly with different socioeconomic organisation of cities. However, we show that relations are sensitive to the way cities are defined and delineated. In several cases, changing the city delineation rule can change the significance and even the sign of the correlation. In general, cities delineated in a restricted way (central cores only) exhibit traces of human activity which are less related to their socioeconomic organisation than cities delineated as metropolitan areas and dispersed urban regions.

Favelas, Affordable Housing, and Authoritarian Urbanism in the Era of Mass Eradication in Rio de Janeiro, 1960s–1970s

2021 ◽  
Author(s):  
Leandro Benmergui
Keyword(s):  
Affordable Housing ◽  
Low Income ◽  
Rio De Janeiro ◽  
Social Science Research ◽  
Urban Infrastructure ◽  
Science Research ◽  
Military Regimes ◽  
The 1960S ◽  
The Right ◽  
The City

As the number of favelas and poor residents of Rio de Janeiro grew quickly by the mid-20th century, they became the object of policymaking, social science research, real estate speculation, and grassroots mobilization. After a decade in which local authorities recognized the de facto presence of favelas but without legally ascertaining the right of permanence, the 1960s and early 1970s witnessed the era of mass eradication. Seemingly contradictory—but complementary—policies also included the development of massive low-income housing complexes and innovative community development and favela urbanization experiences empowered by community organizations with the assistance of experts committed to improving the lives of poor Cariocas (residents of Rio). Favelas in Rio were at the crossroads of a particular interplay of forces: the urgent need to modernize Rio’s obsolete and inadequate urban infrastructure; the new administrative status of the city after the inauguration of Brasilia; and the redefinition of the balance of power between local, municipal, and federal forces in a time of radical politics and authoritarian and technocratic military regimes, Cold War diplomacy, and the transnational flows of expertise and capital.

scholarly journals Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method

2018 ◽  
Vol 10 (7) ◽  
pp. 2432 ◽  
Author(s):  
Lingbo Liu ◽  
Zhenghong Peng ◽  
Hao Wu ◽  
Hongzan Jiao ◽  
Yang Yu
Keyword(s):  
Land Use ◽  
Spatial Heterogeneity ◽  
Mobile Phone ◽  
Census Data ◽  
Base Station ◽  
Distance Decay ◽  
Base Stations ◽  
Mobile Phone Data ◽  
Dasymetric Mapping ◽  
Spatial Feature

Dasymetric mapping of high-resolution population facilitates the exploration of urban spatial feature. While most relevant studies are still challenged by weak spatial heterogeneity of ancillary data and quality of traditional census data, usually outdated, costly and inaccurate, this paper focuses on mobile phone data, which can be real-time and precise, and also strengthens spatial heterogeneity by its massive mobile phone base stations. However, user population recorded by mobile phone base stations have no fixed spatial boundary, and base stations often disperse in extremely uneven spatial distribution, this study defines a distance-decay supply–demand relation between mobile phone user population of gridded base station and its surrounding land patches, and outlines a dasymetric mapping method integrating two-step floating catchment area method (2SFCAe) and land use regression (LUR). The results indicate that LUR-2SFCAe method shows a high fitness of regression, provides population mapping at a finer scale and helps identify urban centrality and employment subcenters with detailed worktime and non-worktime populations. The work involving studies of dasymetric mapping based on LUR-2SFCAe method and mobile phone data proves to be encouraging, sheds light on the relationship between mobile phone users and nearby land use, brings about an integrated exploration of 2SFCAe in LUR with distance-decay effect and enhances spatial heterogeneity.

scholarly journals The time varying network of urban space uses in Milan

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Alba Bernini ◽  
Amadou Lamine Toure ◽  
Renato Casagrandi
Keyword(s):  
Land Use ◽  
Mobile Phone ◽  
Urban Space ◽  
Temporal Analysis ◽  
Mobile Phone Data ◽  
Natural Environments ◽  
Urban Structure ◽  
Land Uses ◽  
Population Mobility ◽  
The City

AbstractIn a metropolis, people movements design intricate patterns that change on very short temporal scales. Population mobility obviously is not random, but driven by the land uses of the city. Such an urban ecosystem can interestingly be explored by integrating the spatial analysis of land uses (through ecological indicators commonly used to characterize natural environments) with the temporal analysis of human mobility (reconstructed from anonymized mobile phone data). Considering the city of Milan (Italy) as a case study, here we aimed to identify the complex relations occurring between the land-use composition of its neighborhoods and the spatio-temporal patterns of occupation made by citizens. We generated two spatially explicit networks, one static and the other temporal, based on the analysis of land uses and mobile phone data, respectively. The comparison between the results of community detection performed on both networks revealed that neighborhoods that are similar in terms of land-use composition are not necessarily characterized by analogous temporal fluctuations of human activities. In particular, the historical concentric urban structure of Milan is still under play. Our big data driven approach to characterize urban diversity provides outcomes that could be important (i) to better understand how and when urban spaces are actually used, and (ii) to allow policy makers improving strategic development plans that account for the needs of metropolis-like permanently changing cities.

The mobile phone between fashion and design

2013 ◽  
Vol 1 (1) ◽  
pp. 102-109 ◽  
Author(s):  
Leopoldina Fortunati
Keyword(s):  
Social Networks ◽  
Social Science ◽  
Mobile Phone ◽  
Social Science Research ◽  
Science Research ◽  
Current Debate

In this article first of all I want to look at the current debate on fashion and the mobile phone. After a brief outline of the question, I discuss the role of fashion and then of design, an interconnected theme that has never been satisfactorily addressed in this debate. Then I analyse briefly how social networks and applications have introduced the discourse surrounding fashion and information about fashion to this device. My conclusion is that it is now necessary to make social science research converge with HCI research in order to have a better understanding of the potentialities of the mobile phone and a clearer vision of where research is now needed.

scholarly journals Quantifying the differences in call detail records

2021 ◽  
Vol 8 (6) ◽  
pp. 201443
Author(s):  
Federico Botta
Keyword(s):  
Mobile Phone ◽  
Computational Social Science ◽  
Text Messages ◽  
Mobile Phone Data ◽  
Data Usage ◽  
Phone Calls ◽  
Different Types ◽  
Changes Over Time ◽  
The Relationship ◽  
Call Detail Records

The increasing availability of mobile phone data has attracted the attention of several researchers interested in studying our collective behaviour. Our interactions with the phone network can take several forms, from SMS messages to phone calls and data usage. Typically, mobile phone data are released to researchers in the form of call detail records , which contain records of different types of interactions, and can be used to analyse various aspects of our behaviour. However, the inherently behavioural nature of these interactions may result in differences between how we make phone calls and receive text messages. Studies which rely on data derived from these interactions, therefore, need to carefully consider these differences. Here, we aim to investigate differences and limitations of different types of mobile phone interactions data by analysing a large mobile phone dataset. We study the relationship between different types of interactions and show how it changes over time. We anticipate our findings to be of interest to all researchers working in the area of computational social science.

Content Analysis

2021 ◽  
pp. 56-62
Author(s):  
Leeann Bass ◽  
Holli A. Semetko
Keyword(s):  
Content Analysis ◽  
Social Science ◽  
Research Method ◽  
Social Science Research ◽  
Science Research ◽  
Computational Social Science ◽  
Qualitative Approach ◽  
Systematic Analysis ◽  
Media Communication ◽  
Inductive Approach

This chapter explains content analysis, which is a social science research method that involves the systematic analysis of text, media, communication, or information. The source, the message, the receiver, the medium, and the influence of the message are all topics that have been studied using content analysis and in combination with other methods. There are deductive and inductive approaches to content analysis. Two widely cited studies using content analysis take a deductive approach: using predefined categories and variables based on findings and best practices from prior research. Studies taking an inductive approach to content analysis, by contrast, have an open view of the content, usually involve a small-N sample, and are often based on a qualitative approach. Meanwhile, much has been written on methods and approaches to measuring reliability with human coders. Traditional content analysis uses human coders, whereas a variety of software has emerged that can be used to download and score or code vast amounts of textual news data. The chapter then identifies key benefits and challenges associated with new computational social science tools such as text analysis.

Taming Big Data

2016 ◽  
Vol 46 (2) ◽  
pp. 189-217 ◽  
Author(s):  
Christopher A. Bail
Keyword(s):  
Social Media ◽  
Social Science ◽  
Nonprofit Organizations ◽  
Collective Behavior ◽  
Social Science Research ◽  
Science Research ◽  
Computational Social Science ◽  
New Method ◽  
Public Attention ◽  
Public Data

Social media websites such as Facebook and Twitter provide an unprecedented amount of qualitative data about organizations and collective behavior. Yet these new data sources lack critical information about the broader social context of collective behavior—or protect it behind strict privacy barriers. In this article, I introduce social media survey apps (SMSAs) that adjoin computational social science methods with conventional survey techniques in order to enable more comprehensive analysis of collective behavior online. SMSAs (1) request large amounts of public and non-public data from organizations that maintain social media pages, (2) survey these organizations to collect additional data of interest to a researcher, and (3) return the results of a scholarly analysis back to these organizations as incentive for them to participate in social science research. SMSAs thus provide a highly efficient, cost-effective, and secure method for extracting detailed data from very large samples of organizations that use social media sites. This article describes how to design and implement SMSAs and discusses an application of this new method to study how nonprofit organizations attract public attention to their cause on Facebook. I conclude by evaluating the quality of the sample derived from this application of SMSAs and discussing the potential of this new method to study non-organizational populations on social media sites as well.

scholarly journals Computational Social Science for Nonprofit Studies: Developing a Toolbox and Knowledge Base for the Field

2021 ◽  
Author(s):  
Ji Ma ◽  
Islam Akef Ebeid ◽  
Arjen de Wit ◽  
Meiying Xu ◽  
Yongzheng Yang ◽  
...  
Keyword(s):  
Social Science ◽  
Social Science Research ◽  
Science Research ◽  
Computational Social Science ◽  
Concept Representation ◽  
Nonprofit Studies ◽  
Knowledge Infrastructure ◽  
Design Perspective ◽  
Philanthropic Studies ◽  
Computationally Intensive

AbstractHow can computational social science (CSS) methods be applied in nonprofit and philanthropic studies? This paper summarizes and explains a range of relevant CSS methods from a research design perspective and highlights key applications in our field. We define CSS as a set of computationally intensive empirical methods for data management, concept representation, data analysis, and visualization. What makes the computational methods “social” is that the purpose of using these methods is to serve quantitative, qualitative, and mixed-methods social science research, such that theorization can have a solid ground. We illustrate the promise of CSS in our field by using it to construct the largest and most comprehensive database of scholarly references in our field, the Knowledge Infrastructure of Nonprofit and Philanthropic Studies (KINPS). Furthermore, we show that through the application of CSS in constructing and analyzing KINPS, we can better understand and facilitate the intellectual growth of our field. We conclude the article with cautions for using CSS and suggestions for future studies implementing CSS and KINPS.

The contingency of neighbourhood diversity: Variation of social context using mobile phone application data

Urban Studies ◽  
2021 ◽  
pp. 004209802110196
Author(s):  
Wenfei Xu
Keyword(s):  
Mobile Phone ◽  
Census Data ◽  
Racial Diversity ◽  
Social Contact ◽  
Social Contexts ◽  
Mobile Phone Application ◽  
Activity Spaces ◽  
Residential Context ◽  
Application Data ◽  
The City

This research uses high-density anonymised mobile phone application (MPA) global-positioning system (GPS) data to describe exposure to racial diversity in different social contexts with an aim to clarify the mechanism linking residential diversity to opportunities for diverse social interactions. In particular, it explores the hypothesis that a diverse residential context does not lead to diverse social contact by comparing three exposure measures – residential, observed and interaction – on the census block group level in Chicago. In doing so, it also explores the contribution of activity spaces to opportunities for diverse social contact. The findings show that the exposure to opportunities for diverse social contact measured by MPA data is generally higher than what is implied by residential census data, especially in areas of high residential segregation in the city. Further, measures using MPA data reveal more spatiotemporal heterogeneity of exposure than that implied by the residential context.

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