book – Page 84 – The Living Library

How to Beat Science and Influence People: Policy Makers and Propaganda in Epistemic Networks

Curated on February 4, 2018August 3, 2018 by Stefaan Verhulst

Paper by James Owen Weatherall, Cailin O’Connor, and Justin Bruner: “In their recent book Merchants of Doubt [New York:Bloomsbury 2010], Naomi Oreskes and Erik Conway describe the “tobacco strategy”, which was used by the tobacco industry to influence policy makers regarding the health risks of tobacco products. The strategy involved two parts, consisting of (1) promoting and sharing independent research supporting the industry’s preferred position and (2) funding additional research, but selectively publishing the results.

We introduce a model of the Tobacco Strategy, and use it to argue that both prongs of the strategy can be extremely effective–even when policy makers rationally update on all evidence available to them. As we elaborate, this model helps illustrate the conditions under which the Tobacco Strategy is particularly successful. In addition, we show how journalists engaged in “fair” reporting can inadvertently mimic the effects of industry on public belief….(More)”.

Earth Observation Open Science and Innovation

Curated on February 4, 2018August 3, 2018 by Stefaan Verhulst

Open Access book edited by Pierre-Philippe Mathieu and Christoph Aubrecht: “Over the past decades, rapid developments in digital and sensing technologies, such as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. The digital transformation is revolutionizing our ability to monitor our planet and transforming the way we access, process and exploit Earth Observation data from satellites.

This book reviews these megatrends and their implications for the Earth Observation community as well as the wider data economy. It provides insight into new paradigms of Open Science and Innovation applied to space data, which are characterized by openness, access to large volume of complex data, wide availability of new community tools, new techniques for big data analytics such as Artificial Intelligence, unprecedented level of computing power, and new types of collaboration among researchers, innovators, entrepreneurs and citizen scientists. In addition, this book aims to provide readers with some reflections on the future of Earth Observation, highlighting through a series of use cases not just the new opportunities created by the New Space revolution, but also the new challenges that must be addressed in order to make the most of the large volume of complex and diverse data delivered by the new generation of satellites….(More)”.

The Tyranny of Metrics

Curated on February 1, 2018August 3, 2018 by Stefaan Verhulst

Book by Jerry Z. Muller on “How the obsession with quantifying human performance threatens our schools, medical care, businesses, and government…

Today, organizations of all kinds are ruled by the belief that the path to success is quantifying human performance, publicizing the results, and dividing up the rewards based on the numbers. But in our zeal to instill the evaluation process with scientific rigor, we’ve gone from measuring performance to fixating on measuring itself. The result is a tyranny of metrics that threatens the quality of our lives and most important institutions. In this timely and powerful book, Jerry Muller uncovers the damage our obsession with metrics is causing–and shows how we can begin to fix the problem.

Filled with examples from education, medicine, business and finance, government, the police and military, and philanthropy and foreign aid, this brief and accessible book explains why the seemingly irresistible pressure to quantify performance distorts and distracts, whether by encouraging “gaming the stats” or “teaching to the test.” That’s because what can and does get measured is not always worth measuring, may not be what we really want to know, and may draw effort away from the things we care about. Along the way, we learn why paying for measured performance doesn’t work, why surgical scorecards may increase deaths, and much more. But metrics can be good when used as a complement to—rather than a replacement for—judgment based on personal experience, and Muller also gives examples of when metrics have been beneficial…(More)”.

Handbook on Participatory Governance

Curated on January 28, 2018August 3, 2018 by Stefaan Verhulst

Book edited by Hubert Heinelt: “Can participatory governance really improve the quality of democracy? Concentrating on democracy beyond governmental structures, this Handbook argues that it is a political task to engage individuals at all levels of governance.

The Handbook on Participatory Governance reveals that transforming governance arrangements does in fact enhance democracy and that the democratic quality of participatory governance is crucial. The contributors reflect on the notion of democracy and participatory governance and how they relate to each other. Case studies are presented from regional, national and international levels, to identify how governance can be turned into a participatory form. With chapters reviewing participatory governance’s role alongside power, science and employment relations, innovative ideas for future progress in participatory governance are presented….(More)”.

They Are Watching You—and Everything Else on the Planet

Curated on January 23, 2018August 3, 2018 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)”.

The Future Computed: Artificial Intelligence and its role in society

Curated on January 17, 2018August 20, 2018 by Stefaan Verhulst

Brad Smith at the Microsoft Blog: “Today Microsoft is releasing a new book, The Future Computed: Artificial Intelligence and its role in society. The two of us have written the foreword for the book, and our teams collaborated to write its contents. As the title suggests, the book provides our perspective on where AI technology is going and the new societal issues it has raised.

On a personal level, our work on the foreword provided an opportunity to step back and think about how much technology has changed our lives over the past two decades and to consider the changes that are likely to come over the next 20 years. In 1998, we both worked at Microsoft, but on opposite sides of the globe. While we lived on separate continents and in quite different cultures, we shared similar experiences and daily routines which were managed by manual planning and movement. Twenty years later, we take for granted the digital world that was once the stuff of science fiction.

Technology – including mobile devices and cloud computing – has fundamentally changed the way we consume news, plan our day, communicate, shop and interact with our family, friends and colleagues. Two decades from now, what will our world look like? At Microsoft, we imagine that artificial intelligence will help us do more with one of our most precious commodities: time. By 2038, personal digital assistants will be trained to anticipate our needs, help manage our schedule, prepare us for meetings, assist as we plan our social lives, reply to and route communications, and drive cars.

Beyond our personal lives, AI will enable breakthrough advances in areas like healthcare, agriculture, education and transportation. It’s already happening in impressive ways.

But as we’ve witnessed over the past 20 years, new technology also inevitably raises complex questions and broad societal concerns. As we look to a future powered by a partnership between computers and humans, it’s important that we address these challenges head on.

How do we ensure that AI is designed and used responsibly? How do we establish ethical principles to protect people? How should we govern its use? And how will AI impact employment and jobs?

To answer these tough questions, technologists will need to work closely with government, academia, business, civil society and other stakeholders. At Microsoft, we’ve identified six ethical principles – fairness, reliability and safety, privacy and security, inclusivity, transparency, and accountability – to guide the cross-disciplinary development and use of artificial intelligence. The better we understand these or similar issues — and the more technology developers and users can share best practices to address them — the better served the world will be as we contemplate societal rules to govern AI.

We must also pay attention to AI’s impact on workers. What jobs will AI eliminate? What jobs will it create? If there has been one constant over 250 years of technological change, it has been the ongoing impact of technology on jobs — the creation of new jobs, the elimination of existing jobs and the evolution of job tasks and content. This too is certain to continue.

Some key conclusions are emerging….

The Future Computed is available here and additional content related to the book can be found here.”

Toward Information Justice

Curated on January 14, 2018August 3, 2018 by Stefaan Verhulst

Book by Jeffrey Alan Johnson: “…presents a theory of information justice that subsumes the question of control and relates it to other issues that influence just social outcomes. Data does not exist by nature. Bureaucratic societies must provide standardized inputs for governing algorithms, a problem that can be understood as one of legibility. This requires, though, converting what we know about social objects and actions into data, narrowing the many possible representations of the objects to a definitive one using a series of translations. Information thus exists within a nexus of problems, data, models, and actions that the social actors constructing the data bring to it.

This opens information to analysis from social and moral perspectives, while the scientistic view leaves us blind to the gains from such analysis—especially to the ways that embedded values and assumptions promote injustice. Toward Information Justice answers a key question for the 21st Century: how can an information-driven society be just?

Many of those concerned with the ethics of data focus on control over data, and argue that if data is only controlled by the right people then just outcomes will emerge. There are serious problems with this control metaparadigm, however, especially related to the initial creation of data and prerequisites for its use. This text is suitable for academics in the fields of information ethics, political theory, philosophy of technology, and science and technology studies, as well as policy professionals who rely on data to reach increasingly problematic conclusions about courses of action….(More)”.

Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor

Curated on January 9, 2018August 3, 2018 by Stefaan Verhulst

Book by Virginia Eubanks: “The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years—because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect.

Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor.

In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile.

The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values….(More)”.

Selected Readings on Data, Gender, and Mobility

Curated on January 9, 2018July 18, 2019 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:

Insights on how data can inform gender empowerment initiatives,
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
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.