The Age of Perplexity: Rethinking the World we Knew

Curated on Posted on by Stefaan Verhulst

BVBA Open Access Book: “The impact of globalization, of technological progress and of the insecurity that they cause is reflected in people’s decisions, and by the path that our society is following. This path that will decide our future, in the sense that it will determine our capability of facing the challenges and taking advantage of the opportunities offered up by the advances in science and technology.

In this book, we look at generalized subjects, taking in the transformation that computing and the greater availability of information brings to our perceptions and understanding of things, and in the social imaginaries, that shape our attitudes and reactions to the events that we observe.
All this underpins the changes in politics we are witnessing, the appearance of populist movements or, more generally, the lack of commitment or disaffection with political institutions and the values that support the existing democracies. In these arenas, the new digital media, new types of digital political activism, and the rise of movements that question the dominant economic and political paradigm all play a key role.

In the supranational and geopolitical level we discuss the importance of incorporating a feminist perspective to international relations (as well, of course, as to all the spheres of human activity); new types of warfare, in which neither the contenders, strategies or media resemble anything we knew before; the huge geopolitical challenge represented by the complex and diverse Arab Islamic question; the end of the brief unipolar world era, with the emergence of powers that question the United States’ hegemony, among which we highlight China; or the future role of Latin America in the global map.

Regarding the economic questions that are at the root of the current perplexity, insecurity and discontent, we examine the impact of globalization and technological change on growth, the welfare state and, above all, employment.

From this base, we look at which are the most suitable economic policies and forms of organization for harnessing the potential of the digital revolution, and also for minimizing the risks of a society with increasing inequality, with a huge number of jobs taken over by machines, or even the loss of control of individual or collective decisions.

This technological revolution will undoubtedly require a complex transition process, but we also have before us a wonderful opportunity to better tend to the needs and demands of people: with more growth, jobs and a fairer distribution of wealth, and a richer and fuller life for the whole of humanity….(More)”.

Empowerment tool for women maps cases of harassment

Curated on Posted on by Stefaan Verhulst

Springwise: “We have previously written about innovations that promote inclusion and equal rights such as edible pie charts that highlight gender inequality. Another example is a predictive text app that finds alternative words for gendered language. Now, NINA, created in Brazil, is an app for empowering women to report violence that occurs in public spaces. The project was shared to Red Bull Amaphiko, a platform for social entrepreneurs to share their work and stories.

A 2016 survey released by ActionAid and conducted by YouGov found that 86 percent of Brazilian women were victims of harassment in public spaces. Responding to these statistics, Simony César created project NINA two years ago to help tackle gender-based violence. The app collects data in real time, mapping locations in which cases of harassment have taken place. The launch and testing of the app took place on public transport. It saw 76 thousand users per day at 17 bus lines at the Federal University of Pernambuco (UFPE).

César states “The premise of NINA aims to empower women through an application that denounces the types of violence they suffer within public spaces”. It combats violence against women by making cases of harassment in the city locatable on a map. NINA can then use this data to find out which bus lines have the highest rate of harassment. It can also record the most common times that cases occur and store photographic records and short videos of harassers.

Another survey by ActionAid in March 2018 revealed that 64 percent of Brazilian women surveyed were victims of sexual harassment. These results demonstrate that the need for empowerment tools, such as NINA, is still necessary. The exposure of women to violence in public city spaces is a global issue and as a result, accessibility within cities is unequal based on gender….(More)”.

Can Data Help Brazil Take a Bite Out of Crime?

Curated on Posted on by Stefaan Verhulst

Joe Leahy at ZY See Beyond: “When Argentine entrepreneur Federico Vega two years ago launched a startup offering Uberlike services for Brazil’s freight industry, the sector was on the cusp of a wave of cargo theft.

Across Brazil, but especially in Rio de Janeiro, crime has soared, with armed gangs robbing one truck every 50 minutes in Rio last year.

But while the authorities have reacted with force to the crime wave, Vega turned to software engineers at his CargoX startup. By studying a range of industry and security data, CargoX developed software that identifies risks and helps drivers avoid crime hot spots, or if a robbery does happen, alerts the company in real time.CargoX says that in Brazil, 0.1 percent by value of all cargo transported by trucks is stolen. “We are about 50 percent lower than that, but we still have tons of work to do,” says São Paulo–based Vega.

CargoX is one of a growing number of Brazilian technology startups that are seeking digital solutions to the problem of endemic crime in Latin America’s largest country.

Having started from zero two years ago, CargoX today has signed up more than 5,000 truckers. The company scans data from all sources to screen its motorists and study past crimes to see what routes, times, neighborhoods and types of cargo represent the highest risk.

Certain gas stations that might, for instance, be known for prostitution are avoided because of their criminal associations. Daytime delivery is better than night. Drivers are tracked by GPS and must stay inside “geofences” — known safe routes. Foraying outside these alerts the system.

Vega says the key is to learn from the data. “Everyone says it’s good to learn from your mistakes, but it’s even better to learn from other people’s mistakes.”

The use of big data to anticipate crime is at the center of the approach of another tech-savvy entrepreneur, Pedro Moura Costa, the founder of BVRio Institute, an organization that seeks market solutions to environmental issues.

Organized crime is targeting everything from highway robbery to the illegal plunder of tropical hardwoods in the Amazon while online crime such as credit card fraud is also rampant, analysts say….(More)”.

Infection forecasts powered by big data

Curated on Posted on by Stefaan Verhulst

Michael Eisenstein at Nature: “…The good news is that the present era of widespread access to the Internet and digital health has created a rich reservoir of valuable data for researchers to dive into….By harvesting and combining these streams of big data with conventional ways of monitoring infectious diseases, the public-health community could gain fresh powers to catch and curb emerging outbreaks before they rage out of control.

Going viral

Data scientists at Google were the first to make a major splash using data gathered online to track infectious diseases. The Google Flu Trends algorithm, launched in November 2008, combed through hundreds of billions of users’ queries on the popular search engine to look for small increases in flu-related terms such as symptoms or vaccine availability. Initial data suggested that Google Flu Trends could accurately map the incidence of flu with a lag of roughly one day. “It was a very exciting use of these data for the purpose of public health,” says Brownstein. “It really did start a whole revolution and new field of work in query data.”

Unfortunately, Google Flu Trends faltered when it mattered the most, completely missing the onset in April 2009 of the H1N1 pandemic. The algorithm also ran into trouble later on in the pandemic. It had been trained against seasonal fluctuations of flu, says Viboud, but people’s behaviour changed in the wake of panic fuelled by media reports — and that threw off Google’s data. …

Nevertheless, its work with Internet usage data was inspirational for infectious-disease researchers. A subsequent study from a team led by Cecilia Marques-Toledo at the Federal University of Minas Gerais in Belo Horizonte, Brazil, used Twitter to get high-resolution data on the spread of dengue fever in the country. The researchers could quickly map new cases to specific cities and even predict where the disease might spread to next (C. A. Marques-Toledo et al. PLoS Negl. Trop. Dis. 11, e0005729; 2017). Similarly, Brownstein and his colleagues were able to use search data from Google and Twitter to project the spread of Zika virus in Latin America several weeks before formal outbreak declarations were made by public-health officials. Both Internet services are used widely, which makes them data-rich resources. But they are also proprietary systems for which access to data is controlled by a third party; for that reason, Generous and his colleagues have opted instead to make use of search data from Wikipedia, which is open source. “You can get the access logs, and how many people are viewing articles, which serves as a pretty good proxy for search interest,” he says.

However, the problems that sank Google Flu Trends still exist….Additionally, online activity differs for infectious conditions with a social stigma such as syphilis or AIDS, because people who are or might be affected are more likely to be concerned about privacy. Appropriate search-term selection is essential: Generous notes that initial attempts to track flu on Twitter were confounded by irrelevant tweets about ‘Bieber fever’ — a decidedly non-fatal condition affecting fans of Canadian pop star Justin Bieber.

Alternatively, researchers can go straight to the source — by using smartphone apps to ask people directly about their health. Brownstein’s team has partnered with the Skoll Global Threats Fund to develop an app called Flu Near You, through which users can voluntarily report symptoms of infection and other information. “You get more detailed demographics about age and gender and vaccination status — things that you can’t get from other sources,” says Brownstein. Ten European Union member states are involved in a similar surveillance programme known as Influenzanet, which has generally maintained 30,000–40,000 active users for seven consecutive flu seasons. These voluntary reporting systems are particularly useful for diseases such as flu, for which many people do not bother going to the doctor — although it can be hard to persuade people to participate for no immediate benefit, says Brownstein. “But we still get a good signal from the people that are willing to be a part of this.”…(More)”.

Open data sharing and the Global South—Who benefits?

Curated on Posted on by Stefaan Verhulst

David Serwadda et al in Science: “A growing number of government agencies, funding organizations, and publishers are endorsing the call for increased data sharing, especially in biomedical research, many with an ultimate goal of open data. Open data is among the least restrictive forms of data sharing, in contrast to managed access mechanisms, which typically have terms of use and in some cases oversight by the data generators themselves. But despite an ethically sound rationale and growing support for open data sharing in many parts of the world, concerns remain, particularly among researchers in low- and middle-income countries (LMICs) in Africa, Latin America, and parts of Asia and the Middle East that comprise the Global South. Drawing on our perspective as researchers and ethicists working in the Global South, we see opportunities to improve community engagement, raise awareness, and build capacity, all toward improving research and data sharing involving researchers in LMICs…African scientists have expressed concern that open data compromises national ownership and reopens the gates for “parachute-research” (i.e., Northern researchers absconding with data to their home countries). Other LMIC researchers have articulated fears over free-riding scientists using the data collected by others for their own career advancement …(More)”

The Rise of Virtual Citizenship

Curated on Posted on by Stefaan Verhulst

James Bridle in The Atlantic: “In Cyprus, Estonia, the United Arab Emirates, and elsewhere, passports can now be bought and sold….“If you believe you are a citizen of the world, you are a citizen of nowhere. You don’t understand what citizenship means,” the British prime minister, Theresa May, declared in October 2016. Not long after, at his first postelection rally, Donald Trump asserted, “There is no global anthem. No global currency. No certificate of global citizenship. We pledge allegiance to one flag and that flag is the American flag.” And in Hungary, Prime Minister Viktor Orbán has increased his national-conservative party’s popularity with statements like “all the terrorists are basically migrants” and “the best migrant is the migrant who does not come.”

Citizenship and its varying legal definition has become one of the key battlegrounds of the 21st century, as nations attempt to stake out their power in a G-Zero, globalized world, one increasingly defined by transnational, borderless trade and liquid, virtual finance. In a climate of pervasive nationalism, jingoism, xenophobia, and ever-building resentment toward those who move, it’s tempting to think that doing so would become more difficult. But alongside the rise of populist, identitarian movements across the globe, identity itself is being virtualized, too. It no longer needs to be tied to place or nation to function in the global marketplace.

Hannah Arendt called citizenship “the right to have rights.” Like any other right, it can be bestowed and withheld by those in power, but in its newer forms it can also be bought, traded, and rewritten. Virtual citizenship is a commodity that can be acquired through the purchase of real estate or financial investments, subscribed to via an online service, or assembled by peer-to-peer digital networks. And as these options become available, they’re also used, like so many technologies, to exclude those who don’t fit in.

In a world that increasingly operates online, geography and physical infrastructure still remain crucial to control and management. Undersea fiber-optic cables trace the legacy of imperial trading routes. Google and Facebook erect data centers in Scandinavia and the Pacific Northwest, close to cheap hydroelectric power and natural cooling. The trade in citizenship itself often manifests locally as architecture. From luxury apartments in the Caribbean and the Mediterranean to data centers in Europe and refugee settlements in the Middle East, a scattered geography of buildings brings a different reality into focus: one in which political decisions and national laws transform physical space into virtual territory…(More)”.

Can scientists learn to make ‘nature forecasts’ just as we forecast the weather?

Curated on Posted on by Stefaan Verhulst

 at The Conversation: “We all take weather forecasts for granted, so why isn’t there a ‘nature forecast’ to answer these questions? Enter the new scientific field of ecological forecasting. Ecologists have long sought to understand the natural world, but only recently have they begun to think systematically about forecasting.

Much of the current research in ecological forecasting is focused on long-term projections. It considers questions that play out over decades to centuries, such as how species may shift their ranges in response to climate change, or whether forests will continue to take up carbon dioxide from the atmosphere.

However, in a new article that I co-authored with 18 other scientists from universities, private research institutes and the U.S. Geological Survey, we argue that focusing on near-term forecasts over spans of days, seasons and years will help us better understand, manage and conserve ecosystems. Developing this ability would be a win-win for both science and society….

Big data is driving many of the advances in ecological forecasting. Today ecologists have orders of magnitude more data compared to just a decade ago, thanks to sustained public funding for basic science and environmental monitoring. This investment has given us better sensors, satellites and organizations such as the National Ecological Observatory Network, which collects high-quality data from 81 field sites across the United States and Puerto Rico. At the same time, cultural shifts across funding agencies, research networks and journals have made that data more open and available.

Digital technologies make it possible to access this information more quickly than in the past. Field notebooks have given way to tablets and cell networks that can stream new data into supercomputers in real time. Computing advances allow us to build better models and use more sophisticated statistical methods to produce forecasts….(More)”.

Is There Something Wrong with Democracy?

Curated on Posted on by Stefaan Verhulst

Max Fisher and Amanda Taub at The New York Times: “After 200 years of expansion, democracy’s growth in the world has stalled. A handful of democracies like Venezuela and Hungary are backsliding into authoritarianism. And even in established Western democracies, voters are losing faith in democratic institutions and norms.

That has left us and scholars who study democracy obsessed with a set of questions. Is this all just a blip, or is democracy in real trouble? Are the oldest and sturdiest democracies, like those of Europe and the United States, really as safe as they seem? And why would people voluntarily dismantle their own democracy from within?

No one knows the answers for sure. But we’re starting to figure them out and it’s not all good news. Here, in the first of what will become a regular series of videos exploring big questions and ideas about the world, we explain what we know about democracy’s troubles, what’s causing them and where it leads….(See VIDEO)”.

They Are Watching You—and Everything Else on the Planet

Curated on Posted on by Stefaan Verhulst

Cover article by Robert Draper for Special Issue of the National Geographic: “Technology and our increasing demand for security have put us all under surveillance. Is privacy becoming just a memory?…

In 1949, amid the specter of European authoritarianism, the British novelist George Orwell published his dystopian masterpiece 1984, with its grim admonition: “Big Brother is watching you.” As unsettling as this notion may have been, “watching” was a quaintly circumscribed undertaking back then. That very year, 1949, an American company released the first commercially available CCTV system. Two years later, in 1951, Kodak introduced its Brownie portable movie camera to an awestruck public.

Today more than 2.5 trillion images are shared or stored on the Internet annually—to say nothing of the billions more photographs and videos people keep to themselves. By 2020, one telecommunications company estimates, 6.1 billion people will have phones with picture-taking capabilities. Meanwhile, in a single year an estimated 106 million new surveillance cameras are sold. More than three million ATMs around the planet stare back at their customers. Tens of thousands of cameras known as automatic number plate recognition devices, or ANPRs, hover over roadways—to catch speeding motorists or parking violators but also, in the case of the United Kingdom, to track the comings and goings of suspected criminals. The untallied but growing number of people wearing body cameras now includes not just police but also hospital workers and others who aren’t law enforcement officers. Proliferating as well are personal monitoring devices—dash cams, cyclist helmet cameras to record collisions, doorbells equipped with lenses to catch package thieves—that are fast becoming a part of many a city dweller’s everyday arsenal. Even less quantifiable, but far more vexing, are the billions of images of unsuspecting citizens captured by facial-recognition technology and stored in law enforcement and private-sector databases over which our control is practically nonexistent.

Those are merely the “watching” devices that we’re capable of seeing. Presently the skies are cluttered with drones—2.5 million of which were purchased in 2016 by American hobbyists and businesses. That figure doesn’t include the fleet of unmanned aerial vehicles used by the U.S. government not only to bomb terrorists in Yemen but also to help stop illegal immigrants entering from Mexico, monitor hurricane flooding in Texas, and catch cattle thieves in North Dakota. Nor does it include the many thousands of airborne spying devices employed by other countries—among them Russia, China, Iran, and North Korea.

We’re being watched from the heavens as well. More than 1,700 satellites monitor our planet. From a distance of about 300 miles, some of them can discern a herd of buffalo or the stages of a forest fire. From outer space, a camera clicks and a detailed image of the block where we work can be acquired by a total stranger….

This is—to lift the title from another British futurist, Aldous Huxley—our brave new world. That we can see it coming is cold comfort since, as Carnegie Mellon University professor of information technology Alessandro Acquisti says, “in the cat-and-mouse game of privacy protection, the data subject is always the weaker side of the game.” Simply submitting to the game is a dispiriting proposition. But to actively seek to protect one’s privacy can be even more demoralizing. University of Texas American studies professor Randolph Lewis writes in his new book, Under Surveillance: Being Watched in Modern America, “Surveillance is often exhausting to those who really feel its undertow: it overwhelms with its constant badgering, its omnipresent mysteries, its endless tabulations of movements, purchases, potentialities.”

The desire for privacy, Acquisti says, “is a universal trait among humans, across cultures and across time. You find evidence of it in ancient Rome, ancient Greece, in the Bible, in the Quran. What’s worrisome is that if all of us at an individual level suffer from the loss of privacy, society as a whole may realize its value only after we’ve lost it for good.”…(More)”.

Selected Readings on Data, Gender, and Mobility

Curated on Posted on by Michelle Winowatan

By Michelle Winowatan, Andrew Young, and Stefaan Verhulst

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of data, gender, and mobility was originally published in 2017.

This edition of the Selected Readings was  developed as part of an ongoing project at the GovLab, supported by Data2X, in collaboration with UNICEF, DigitalGlobe, IDS (UDD/Telefonica R&D), and the ISI Foundation, to establish a data collaborative to analyze unequal access to urban transportation for women and girls in Chile. We thank all our partners for their suggestions to the below curation – in particular Leo Ferres at IDS who got us started with this collection; Ciro Cattuto and Michele Tizzoni from the ISI Foundation; and Bapu Vaitla at Data2X for their pointers to the growing data and mobility literature. 

Introduction

Daily mobility is key for gender equity. Access to transportation contributes to women’s agency and independence. The ability to move from place to place safely and efficiently can allow women to access education, work, and the public domain more generally. Yet, mobility is not just a means to access various opportunities. It is also a means to enter the public domain.

Women’s mobility is a multi-layered challenge
Women’s daily mobility, however, is often hampered by social, cultural, infrastructural, and technical barriers. Cultural bias, for instance, limits women mobility in a way that women are confined to an area with close proximity to their house due to society’s double standard on women to be homemakers. From an infrastructural perspective, public transportation mostly only accommodates home-to-work trips, when in reality women often make more complex trips with stops, for example, at the market, school, healthcare provider – sometimes called “trip chaining.” From a safety perspective, women tend to avoid making trips in certain areas and/or at certain time, due to a constant risk of being sexually harassed on public places. Women are also pushed toward more expensive transportation – such as taking a cab instead of a bus or train – based on safety concerns.

The growing importance of (new sources of) data
Researchers are increasingly experimenting with ways to address these interdependent problems through the analysis of diverse datasets, often collected by private sector businesses and other non-governmental entities. Gender-disaggregated mobile phone records, geospatial data, satellite imagery, and social media data, to name a few, are providing evidence-based insight into gender and mobility concerns. Such data collaboratives – the exchange of data across sectors to create public value – can help governments, international organizations, and other public sector entities in the move toward more inclusive urban and transportation planning, and the promotion of gender equity.
The below curated set of readings seek to focus on the following areas:

  1. Insights on how data can inform gender empowerment initiatives,
  2. Emergent research into the capacity of new data sources – like call detail records (CDRs) and satellite imagery – to increase our understanding of human mobility patterns, and
  3. Publications exploring data-driven policy for gender equity in mobility.

Readings are listed in alphabetical order.

We selected the readings based upon their focus (gender and/or mobility related); scope and representativeness (going beyond one project or context); type of data used (such as CDRs and satellite imagery); and date of publication.

Annotated Reading List

Data and Gender

Blumenstock, Joshua, and Nathan Eagle. Mobile Divides: Gender, Socioeconomic Status, and Mobile Phone Use in Rwanda. ACM Press, 2010.

  • Using traditional survey and mobile phone operator data, this study analyzes gender and socioeconomic divides in mobile phone use in Rwanda, where it is found that the use of mobile phones is significantly more prevalent in men and the higher class.
  • The study also shows the differences in the way men and women use phones, for example: women are more likely to use a shared phone than men.
  • The authors frame their findings around gender and economic inequality in the country to the end of providing pointers for government action.

Bosco, Claudio, et al. Mapping Indicators of Female Welfare at High Spatial Resolution. WorldPop and Flowminder, 2015.

  • This report focuses on early adolescence in girls, which often comes with higher risk of violence, fewer economic opportunity, and restrictions on mobility. Significant data gaps, methodological and ethical issues surrounding data collection for girls also create barriers for policymakers to create evidence-based policy to address those issues.
  • The authors analyze geolocated household survey data, using statistical models and validation techniques, and creates high-resolution maps of various sex-disaggregated indicators, such as nutrition level, access to contraception, and literacy, to better inform local policy making processes.
  • Further, it identifies the gender data gap and issues surrounding gender data collection, and provides arguments for why having a comprehensive data can help create better policy and contribute to the achievements of the Sustainable Development Goals (SDGs).

Buvinic, Mayra, Rebecca Furst-Nichols, and Gayatri Koolwal. Mapping Gender Data Gaps. Data2X, 2014.

  • This study identifies gaps in gender data in developing countries on health, education, economic opportunities, political participation, and human security issues.
  • It recommends ways to close the gender data gap through censuses and micro-level surveys, service and administrative records, and emphasizes how “big data” in particular can fill the missing data that will be able to measure the progress of women and girls well being. The authors argue that dentifying these gaps is key to advancing gender equality and women’s empowerment, one of the SDGs.

Catalyzing Inclusive FInancial System: Chile’s Commitment to Women’s Data. Data2X, 2014.

  • This article analyzes global and national data in the banking sector to fill the gap of sex-disaggregated data in Chile. The purpose of the study is to describe the difference in spending behavior and priorities between women and men, identify the challenges for women in accessing financial services, and create policies that promote women inclusion in Chile.

Ready to Measure: Twenty Indicators for Monitoring SDG Gender Targets. Open Data Watch and Data2X, 2016.

  • Using readily available data this study identifies 20 SDG indicators related to gender issues that can serve as a baseline measurement for advancing gender equality, such as percentage of women aged 20-24 who were married or in a union before age 18 (child marriage), proportion of seats held by women in national parliament, and share of women among mobile telephone owners, among others.

Ready to Measure Phase II: Indicators Available to Monitor SDG Gender Targets. Open Data Watch and Data2X, 2017.

  • The Phase II paper is an extension of the Ready to Measure Phase I above. Where Phase I identifies the readily available data to measure women and girls well-being, Phase II provides informations on how to access and summarizes insights from this data.
  • Phase II elaborates the insights about data gathered from ready to measure indicators and finds that although underlying data to measure indicators of women and girls’ wellbeing is readily available in most cases, it is typically not sex-disaggregated.
  • Over one in five – 53 out of 232 – SDG indicators specifically refer to women and girls. However, further analysis from this study reveals that at least 34 more indicators should be disaggregated by sex. For instance, there should be 15 more sex-disaggregated indicators for SDG number 3: “Ensure healthy lives and promote well-being for all at all ages.”
  • The report recommends national statistical agencies to take the lead and assert additional effort to fill the data gap by utilizing tools such as the statistical model to fill the current gender data gap for each of the SDGs.

Reed, Philip J., Muhammad Raza Khan, and Joshua Blumenstock. Observing gender dynamics and disparities with mobile phone metadata. International Conference on Information and Communication Technologies and Development (ICTD), 2016.

  • The study analyzes mobile phone logs of millions of Pakistani residents to explore whether there is a difference in mobile phone usage behavior between male and female and determine the extent to which gender inequality is reflected in mobile phone usage.
  • It utilizes mobile phone data to analyze the pattern of usage behavior between genders, and socioeconomic and demographic data obtained from census and advocacy groups to assess the state of gender equality in each region in Pakistan.
  • One of its findings is a strong positive correlation between proportion of female mobile phone users and education score.

Stehlé, Juliette, et al. Gender homophily from spatial behavior in a primary school: A sociometric study. 2013.

    • This paper seeks to understand homophily, a human behavior characterizes by interaction with peers who have similarities in “physical attributes to tastes or political opinions”. Further, it seeks to identify the magnitude of influence, a type of homophily has to social structures.
    • Focusing on gender interaction among primary school aged children in France, this paper collects data from wearable devices from 200 children in the period of 2 days and measure the physical proximity and duration of the interaction among those children in the playground.
  • It finds that interaction patterns are significantly determined by grade and class structure of the school. Meaning that children belonging to the same class have most interactions, and that lower grades usually do not interact with higher grades.
  • From a gender lens, this study finds that mixed-gender interaction lasts shorter relative to same-gender interaction. In addition, interaction among girls is also longer compared to interaction among boys. These indicate that the children in this school tend to have stronger relationships within their own gender, or what the study calls gender homophily. It further finds that gender homophily is apparent in all classes.

Data and Mobility

Bengtsson, Linus, et al. Using Mobile Phone Data to Predict the Spatial Spread of Cholera. Flowminder, 2015.

  • This study seeks to predict the 2010 cholera epidemic in Haiti using 2.9 million anonymous mobile phone SIM cards and reported cases of Cholera from the Haitian Directorate of Health, where 78 study areas were analyzed in the period of October 16 – December 16, 2010.
  • From this dataset, the study creates a mobility matrix that indicates mobile phone movement from one study area to another and combines that with the number of reported case of cholera in the study areas to calculate the infectious pressure level of those areas.
  • The main finding of its analysis shows that the outbreak risk of a study area correlates positively with the infectious pressure level, where an infectious pressure of over 22 results in an outbreak within 7 days. Further, it finds that the infectious pressure level can inform the sensitivity and specificity of the outbreak prediction.
  • It hopes to improve infectious disease containment by identifying areas with highest risks of outbreaks.

Calabrese, Francesco, et al. Understanding Individual Mobility Patterns from Urban Sensing Data: A Mobile Phone Trace Example. SENSEable City Lab, MIT, 2012.

  • This study compares mobile phone data and odometer readings from annual safety inspections to characterize individual mobility and vehicular mobility in the Boston Metropolitan Area, measured by the average daily total trip length of mobile phone users and average daily Vehicular Kilometers Traveled (VKT).
  • The study found that, “accessibility to work and non-work destinations are the two most important factors in explaining the regional variations in individual and vehicular mobility, while the impacts of populations density and land use mix on both mobility measures are insignificant.” Further, “a well-connected street network is negatively associated with daily vehicular total trip length.”
  • This study demonstrates the potential for mobile phone data to provide useful and updatable information on individual mobility patterns to inform transportation and mobility research.

Campos-Cordobés, Sergio, et al. “Chapter 5 – Big Data in Road Transport and Mobility Research.” Intelligent Vehicles. Edited by Felipe Jiménez. Butterworth-Heinemann, 2018.

  • This study outlines a number of techniques and data sources – such as geolocation information, mobile phone data, and social network observation – that could be leveraged to predict human mobility.
  • The authors also provide a number of examples of real-world applications of big data to address transportation and mobility problems, such as transport demand modeling, short-term traffic prediction, and route planning.

Lin, Miao, and Wen-Jing Hsu. Mining GPS Data for Mobility Patterns: A Survey. Pervasive and Mobile Computing vol. 12,, 2014.

  • This study surveys the current field of research using high resolution positioning data (GPS) to capture mobility patterns.
  • The survey focuses on analyses related to frequently visited locations, modes of transportation, trajectory patterns, and placed-based activities. The authors find “high regularity” in human mobility patterns despite high levels of variation among the mobility areas covered by individuals.

Phithakkitnukoon, Santi, Zbigniew Smoreda, and Patrick Olivier. Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data. PLoS ONE, 2012.

  • This study used a year’s call logs and location data of approximately one million mobile phone users in Portugal to analyze the association between individuals’ mobility and their social networks.
  • It measures and analyze travel scope (locations visited) and geo-social radius (distance from friends, family, and acquaintances) to determine the association.
  • It finds that 80% of places visited are within 20 km of an individual’s nearest social ties’ location and it rises to 90% at 45 km radius. Further, as population density increases, distance between individuals and their social networks decreases.
  • The findings in this study demonstrates how mobile phone data can provide insights to “the socio-geography of human mobility”.

Semanjski, Ivana, and Sidharta Gautama. Crowdsourcing Mobility Insights – Reflection of Attitude Based Segments on High Resolution Mobility Behaviour Data. vol. 71, Transportation Research, 2016.

  • Using cellphone data, this study maps attitudinal segments that explain how age, gender, occupation, household size, income, and car ownership influence an individual’s mobility patterns. This type of segment analysis is seen as particularly useful for targeted messaging.
  • The authors argue that these time- and space-specific insights could also provide value for government officials and policymakers, by, for example, allowing for evidence-based transportation pricing options and public sector advertising campaign placement.

Silveira, Lucas M., et al. MobHet: Predicting Human Mobility using Heterogeneous Data Sources. vol. 95, Computer Communications , 2016.

  • This study explores the potential of using data from multiple sources (e.g., Twitter and Foursquare), in addition to GPS data, to provide a more accurate prediction of human mobility. This heterogenous data captures popularity of different locations, frequency of visits to those locations, and the relationships among people who are moving around the target area. The authors’ initial experimentation finds that the combination of these sources of data are demonstrated to be more accurate in identifying human mobility patterns.

Wilson, Robin, et al. Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake. PLOS Current Disasters, 2016.

  • Utilizing call detail records of 12 million mobile phone users in Nepal, this study seeks spatio-temporal details of the population after the earthquake on April 25, 2015.
  • It seeks to answer the problem of slow and ineffective disaster response, by capturing near real-time displacement pattern provided by mobile phone call detail records, in order to inform humanitarian agencies on where to distribute their assistance. The preliminary results of this study were available nine days after the earthquake.
  • This project relies on the foundational cooperation with mobile phone operator, who supplied the de-identified data from 12 million users, before the earthquake.
  • The study finds that shortly after the earthquake there was an anomalous population movement out of the Kathmandu Valley, the most impacted area, to surrounding areas. The study estimates 390,000 people above normal had left the valley.

Data, Gender and Mobility

Althoff, Tim, et al. “Large-Scale Physical Activity Data Reveal Worldwide Activity Inequality.” Nature, 2017.

  • This study’s analysis of worldwide physical activity is built on a dataset containing 68 million days of physical activity of 717,527 people collected through their smartphone accelerometers.
  • The authors find a significant reduction in female activity levels in cities with high active inequality, where high active inequality is associated with low city walkability – walkability indicators include pedestrian facilities (city block length, intersection density, etc.) and amenities (shops, parks, etc.).
  • Further, they find that high active inequality is associated with high levels of inactivity-related health problems, like obesity.

Borker, Girija. “Safety First: Street Harassment and Women’s Educational Choices in India.” Stop Street Harassment, 2017.

  • Using data collected from SafetiPin, an application that allows user to mark an area on a map as safe or not, and Safecity, another application that lets users share their experience of harassment in public places, the researcher analyzes the safety of travel routes surrounding different colleges in India and their effect on women’s college choices.
  • The study finds that women are willing to go to a lower ranked college in order to avoid higher risk of street harassment. Women who choose the best college from their set of options, spend an average of $250 more each year to access safer modes of transportation.

Frias-Martinez, Vanessa, Enrique Frias-Martinez, and Nuria Oliver. A Gender-Centric Analysis of Calling Behavior in a Developing Economy Using Call Detail Records. Association for the Advancement of Articial Intelligence, 2010.

  • Using encrypted Call Detail Records (CDRs) of 10,000 participants in a developing economy, this study analyzes the behavioral, social, and mobility variables to determine the gender of a mobile phone user, and finds that there is a difference in behavioral and social variables in mobile phone use between female and male.
  • It finds that women have higher usage of phone in terms of number of calls made, call duration, and call expenses compared to men. Women also have bigger social network, meaning that the number of unique phone numbers that contact or get contacted is larger. It finds no statistically significant difference in terms of distance made between calls in men and women.
  • Frias-Martinez et al recommends to take these findings into consideration when designing a cellphone based service.

Psylla, Ioanna, Piotr Sapiezynski, Enys Mones, Sune Lehmann. “The role of gender in social network organization.” PLoS ONE 12, December 20, 2017.

  • Using a large dataset of high resolution data collected through mobile phones, as well as detailed questionnaires, this report studies gender differences in a large cohort. The researchers consider mobility behavior and individual personality traits among a group of more than 800 university students.
  • Analyzing mobility data, they find both that women visit more unique locations over time, and that they have more homogeneous time distribution over their visited locations than men, indicating the time commitment of women is more widely spread across places.

Vaitla, Bapu. Big Data and the Well-Being of Women and Girls: Applications on the Social Scientific Frontier. Data2X, Apr. 2017.

  • In this study, the researchers use geospatial data, credit card and cell phone information, and social media posts to identify problems–such as malnutrition, education, access to healthcare, mental health–facing women and girls in developing countries.
  • From the credit card and cell phone data in particular, the report finds that analyzing patterns of women’s spending and mobility can provide useful insight into Latin American women’s “economic lifestyles.”
  • Based on this analysis, Vaitla recommends that various untraditional big data be used to fill gaps in conventional data sources to address the common issues of invisibility of women and girls’ data in institutional databases.