Child pornography—better known as child sexual abuse material (CSAM)—represents a severe form of exploitation and victimization of children, leaving the victims with emotional and physical trauma. This study presents an analysis of local patterns of CSAM consumption across 1341 French communes in 20 metropolitan regions of France between March 16 to May 31, 2019, using fine-grained mobile traffic data of … Read More
Using Facebook Advertising Data to Describe the Socio-Economic Situation of Syrian Refugees in Lebanon
While the fighting in the Syrian civil war has mostly stopped, an estimated 5.6 million Syrians remain living in neighboring countries.Of these, an estimated 1.5 million are sheltering in Lebanon. Ongoing efforts by organizations such as UNHCR to support the refugee population are often ineffective in reaching those most in need. According to UNHCR’s 2019 Vulnerability Assessment of Syrian Refugees … Read More
Parallel Worlds: Revealing the Inequity of Access to Urban Spaces in Mexico City Through Mobility Data
The near-ubiquitous use of mobile devices generates mobility data that can paint pictures of urban behavior at unprecedented levels of granularity and complexity. In the current period of intense sociopolitical polarization, mobility data can help reveal which urban spaces serve to attenuate or accentuate socioeconomic divides. If urban spaces served to bridge class divides, people from different socioeconomic groups would … Read More
Analyzing the Effect of Time in Migration Measurement Using Georeferenced Digital Trace Data
Georeferenced digital trace data offer unprecedented flexibility in migration estimation. Because of their high temporal granularity, many migration estimates can be generated from the same data set by changing the definition parameters. Yet despite the growing application of digital trace data to migration research, strategies for taking advantage of their temporal granularity remain largely underdeveloped. In this paper, we provide … Read More
Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle
The coronavirus 2019–2020 pandemic (COVID-19) poses unprecedented challenges for governments and societies around the world. Non-pharmaceutical interventions have proven to be critical for delaying and containing the COVID-19 pandemic. These include testing and tracing, bans on large gatherings, nonessential business and school and university closures, international and domestic mobility restrictions and physical isolation, and total lockdowns of regions and countries. … Read More
Using Misinformation as a Political Weapon: COVID-19 and Bolsonaro in Brazil
With over 30,000 confirmed cases, Brazil is currently the country most affected by COVID-19 in Latin America and ranked 12th worldwide. Despite all evidence, a strong rhetoric undermining risks associated to COVID-19 has been endorsed at the highest levels of the Brazilian government, making President Jair Bolsonaro the leader of the “coronavirus-denial movement”. To support this strategy, different forms of … Read More
The ABCDE of Big Data: Assessing Biases in Call-Detail Records for Development Estimates
CDRs (Call Detail Records) represent an important and largely untapped source of data for the developing world. However, they are not representative of the underlying population. We combine CDRs and census data for Senegal in 2013 to evaluate biases related to estimates of population density. We show that: (i) there are systematic relationships between cell-phone use and socio-economic and geographic … Read More
Book Chapter: “Guide to Mobile Data Analytics in Refugee Scenarios”
This book summarizes the most important findings of the Data for Refugees (D4R) Challenge, which was a non-profit project initiated to improve the conditions of the Syrian refugees in Turkey by providing a database for the scientific community to enable research on urgent problems concerning refugees. The database, based on anonymized mobile call detail records (CDRs) of phone calls and … Read More
Retrouver le sens de la mesure pour de meilleures décisions collectives: vers une intelligence artificielle humaine à l’ère des données (p. 47 à 55)
Les données personnelles et institutionnelles récoltées de plus en plus massivement à l’échelle mondiale ouvrent la voie à de nouvelles façons de penser la prise de décision collective. Cet article présente les conditions d’un traitement de ces données tourné vers le développement humain, au travers du concept d’Intelligence Artificielle Humaine (IAH). Nous présentons à cet égard un exemple de projet … Read More
Towards a Human Artificial Intelligence for Human Development
This paper discusses the possibility of applying the key principles and tools of current artificial intelligence (AI) to design future human systems in ways that could make them more efficient, fair, responsive, and inclusive.
On the privacy conscientious use of mobile phone data
The breadcrumbs we leave behind when using our mobile phones—who somebody calls, for how long, and from where—contain unprecedented insights about us and our societies. Researchers have compared the recent availability of large-scale behavioral datasets, such as the ones generated by mobile phones, to the invention of the microscope, giving rise to the new field of computational social science.
Moves on the Street: Classifying Crime Hotspots Using Aggregated Anonymized Data on People Dynamics
This paper highlights the potential societal benefits derived from big data applications with a focus on citizen safety and crime prevention. Authors detail a case study tackling the problem of crime hotspot classification, that is, the classification of which areas in a city are more likely to witness crimes based on past data. In the proposed approach demographic information is … Read More