Western Europe

Behavioral Economics: Are Nudges Cost-Effective?

Curated on April 12, 2018August 3, 2018 by Stefaan Verhulst

Carla Fried at UCLA Anderson Review: “Behavioral science does not suffer from a lack of academic focus. A Google Scholar search for the term delivers more than three million results.

While there is an abundance of research into how human nature can muck up our decision making process and the potential for well-placed nudges to help guide us to better outcomes, the field has kept rather mum on a basic question: Are behavioral nudges cost-effective?

That’s an ever more salient question as the art of the nudge is increasingly being woven into public policy initiatives. In 2009, the Obama administration set up a nudge unit within the White House Office of Information and Technology, and a year later the U.K. government launched its own unit. Harvard’s Cass Sunstein, co-author of the book Nudge, headed the U.S. effort. His co-author, the University of Chicago’s Richard Thaler — who won the 2017 Nobel Prize in Economics — helped develop the U.K.’s Behavioral Insights office. Nudge units are now humming away in other countries, including Germany and Singapore, as well as at the World Bank, various United Nations agencies and the Organisation for Economic Co-operation and Development (OECD).

Given the interest in the potential for behavioral science to improve public policy outcomes, a team of nine experts, including UCLA Anderson’s Shlomo Benartzi, Sunstein and Thaler, set out to explore the cost-effectiveness of behavioral nudges relative to more traditional forms of government interventions.

In addition to conducting their own experiments, the researchers looked at published research that addressed four areas where public policy initiatives aim to move the needle to improve individuals’ choices: saving for retirement, applying to college, energy conservation and flu vaccinations.

For each topic, they culled studies that focused on both nudge approaches and more traditional mandates such as tax breaks, education and financial incentives, and calculated cost-benefit estimates for both types of studies. Research used in this study was published between 2000 and 2015. All cost estimates were inflation-adjusted…

The study itself should serve as a nudge for governments to consider adding nudging to their policy toolkits, as this approach consistently delivered a high return on investment, relative to traditional mandates and policies….(More)”.

A Clever Smartphone Attachment Will Show if Water Is Contaminated

Curated on March 26, 2018August 3, 2018 by Stefaan Verhulst

Victor Tangermann in Futurism: “…astronomers from the University of Leiden in the Netherlands… are developing a simple smartphone attachment that makes it ridiculously, comically easy to measure the quality of water by pointing the tool at it, nothing more.

The tool’s primary purpose isn’t just so that you can whet your whistle in any lake, river, or creek you deem tasty-looking — quick and precise measurements of water pollution can be hugely beneficial for science. This kind of data can steer environmental policies on a national level. Citizens can tell if their drinking water is contaminated. Fishermen are able to determine the quality of their catch, and how pollution could affect local fish populations. Polluted water can even determine human migration patterns by forcing fishermen to move or give up their trade altogether….

There’s a precedent that have researchers hopeful. In 2013, the same team of astronomers and toxicologists developed the iSPEX (Spectropolarimeter for Planetary EXploration) — a smartphone attachment that can measure air pollution. Dutch citizens, along with people in cities from Athens to London, took thousands of measurements of the particulates in the air. The result: a detailed map of dust particles over the Netherlands and beyond.

The technology behind the smartphone attachment actually is a spin-off of sophisticated astronomy technology that can tell if oxygen is present on planets around other stars. This also foregoes the need to take local samples and send them back to the lab — a relatively expensive process that can take a lot longer….(More)”.

Exploring the Motives of Citizen Reporting Engagement: Self-Concern and Other-Orientation

Curated on March 8, 2018August 3, 2018 by Stefaan Verhulst

Paper by Gabriel Abu-Tayeh, Oliver Neumann and Matthias Stuermer: “In smart city contexts, voluntary citizen reporting can be a particularly valuable source of information for local authorities. A key question in this regard is what motivates citizens to contribute their data. Drawing on motivation research in social psychology, the paper examines the question of whether self-concern or other-orientation is a stronger driver of citizen reporting engagement.

To test their hypotheses, the authors rely on a sample of users from the mobile application “Zurich as good as new” in Switzerland, which enables citizens to report damages in and other issues with the city’s infrastructure. Data was collected from two different sources: motivation was assessed in an online user survey (n = 650), whereas citizen reporting engagement was measured by the number of reports per user from real platform-use data. The analysis was carried out using negative binomial regression.

The findings suggest that both self-concern and other-orientation are significant drivers of citizen reporting engagement, although the effect of self-concern appears to be stronger in comparison. As such, this study contributes to a better understanding of what motivates citizens to participate in citizen reporting platforms, which are a cornerstone application in many smart cities….(More)”.

When citizens set the budget: lessons from ancient Greece

Curated on February 19, 2018May 29, 2019 by Stefaan Verhulst

David M. Pritchard and Lyn Carson in The Conversation: “Today elected representatives take the tough decisions about public finances behind closed doors. In doing so, democratic politicians rely on the advice of financial bureaucrats, who, often, cater to the political needs of the elected government. Politicians rarely ask voters what they think of budget options. They are no better at explaining the reasons for a budget. Explanations are usually no more than vacuous phrases, such as “jobs and growth” or “on the move”. They never explain the difficult trade-offs that go into a budget nor their overall financial reasoning.

This reluctance to explain public finances was all too evident during the global financial crisis.

In Australia, Britain and France, centre-left governments borrowed huge sums in order to maintain private demand and, in one case, to support private banks. In each country these policies helped a lot to minimise the crisis’s human costs.

Yet, in the elections that followed the centre-left politicians that had introduced these policies refused properly to justify them. They feared that voters would not tolerate robust discussion about public finances. Without a justification for their generally good policies each of these government was defeated by centre-right opponents.

In most democracies there is the same underlying problem: elected representatives do not believe that voters can tolerate the financial truth. They assume that democracy is not good at managing public finances. For them it can only balance the budget by leaving voters in the dark.

For decades, we, independently, have studied democracy today and in the ancient past. We have learned that this assumption is dead wrong. There are more and more examples of how involving ordinary voters results in better budgets.

In 1989, councils in poor Brazilian towns began to involve residents in setting budgets. This participatory budgeting soon spread throughout South America. It has now been successfully tried in Germany, Spain, Italy, Portugal, Sweden, the United States, Poland and Australia, and some pilot projects were set up in France too. Participatory budgeting is based on the clear principle that those who will be most affected by a tough budget should be involved in setting it.

In spite of such successful democratic experiments, elected representatives still shy away from involving ordinary voters in setting budgets. This is very different from what happened in ancient Athens 2,500 years ago….

In Athenian democracy ordinary citizens actually set the budget. This ancient Greek state had a solid budget, in spite of, or, we would say, because of the involvement of the citizens in taking tough budget decisions….(More)”.

Free Speech in the Filter Age

Curated on February 18, 2018August 3, 2018 by Stefaan Verhulst

Alexandra Borchardt at Project Syndicate: “In a democracy, the rights of the many cannot come at the expense of the rights of the few. In the age of algorithms, government must, more than ever, ensure the protection of vulnerable voices, even erring on victims’ side at times.

Germany’s Network Enforcement Act – according to which social-media platforms like Facebook and YouTube could be fined €50 million ($63 million) for every “obviously illegal” post within 24 hours of receiving a notification – has been controversial from the start. After it entered fully into effect in January, there was a tremendous outcry, with critics from all over the political map arguing that it was an enticement to censorship. Government was relinquishing its powers to private interests, they protested.

So, is this the beginning of the end of free speech in Germany?

Of course not. To be sure, Germany’s Netzwerkdurchsetzungsgesetz (or NetzDG) is the strictest regulation of its kind in a Europe that is growing increasingly annoyed with America’s powerful social-media companies. And critics do have some valid points about the law’s weaknesses. But the possibilities for free expression will remain abundant, even if some posts are deleted mistakenly.

The truth is that the law sends an important message: democracies won’t stay silent while their citizens are exposed to hateful and violent speech and images – content that, as we know, can spur real-life hate and violence. Refusing to protect the public, especially the most vulnerable, from dangerous content in the name of “free speech” actually serves the interests of those who are already privileged, beginning with the powerful companies that drive the dissemination of information.

Speech has always been filtered. In democratic societies, everyone has the right to express themselves within the boundaries of the law, but no one has ever been guaranteed an audience. To have an impact, citizens have always needed to appeal to – or bypass – the “gatekeepers” who decide which causes and ideas are relevant and worth amplifying, whether through the media, political institutions, or protest.

The same is true today, except that the gatekeepers are the algorithms that automatically filter and rank all contributions. Of course, algorithms can be programmed any way companies like, meaning that they may place a premium on qualities shared by professional journalists: credibility, intelligence, and coherence.

But today’s social-media platforms are far more likely to prioritize potential for advertising revenue above all else. So the noisiest are often rewarded with a megaphone, while less polarizing, less privileged voices are drowned out, even if they are providing the smart and nuanced perspectives that can truly enrich public discussions….(More)”.

An AI That Reads Privacy Policies So That You Don’t Have To

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

Andy Greenberg at Wired: “…Today, researchers at Switzerland’s Federal Institute of Technology at Lausanne (EPFL), the University of Wisconsin and the University of Michigan announced the release of Polisis—short for “privacy policy analysis”—a new website and browser extension that uses their machine-learning-trained app to automatically read and make sense of any online service’s privacy policy, so you don’t have to.

In about 30 seconds, Polisis can read a privacy policy it’s never seen before and extract a readable summary, displayed in a graphic flow chart, of what kind of data a service collects, where that data could be sent, and whether a user can opt out of that collection or sharing. Polisis’ creators have also built a chat interface they call Pribot that’s designed to answer questions about any privacy policy, intended as a sort of privacy-focused paralegal advisor. Together, the researchers hope those tools can unlock the secrets of how tech firms use your data that have long been hidden in plain sight….

Polisis isn’t actually the first attempt to use machine learning to pull human-readable information out of privacy policies. Both Carnegie Mellon University and Columbia have made their own attempts at similar projects in recent years, points out NYU Law Professor Florencia Marotta-Wurgler, who has focused her own research on user interactions with terms of service contracts online. (One of her own studies showed that only .07 percent of users actually click on a terms of service link before clicking “agree.”) The Usable Privacy Policy Project, a collaboration that includes both Columbia and CMU, released its own automated tool to annotate privacy policies just last month. But Marotta-Wurgler notes that Polisis’ visual and chat-bot interfaces haven’t been tried before, and says the latest project is also more detailed in how it defines different kinds of data. “The granularity is really nice,” Marotta-Wurgler says. “It’s a way of communicating this information that’s more interactive.”…(More)”.

Improving refugee integration through data-driven algorithmic assignment

Curated on January 23, 2018August 3, 2018 by Stefaan Verhulst

Kirk Bansak, et al in Science Magazine: “Developed democracies are settling an increased number of refugees, many of whom face challenges integrating into host societies. We developed a flexible data-driven algorithm that assigns refugees across resettlement locations to improve integration outcomes. The algorithm uses a combination of supervised machine learning and optimal matching to discover and leverage synergies between refugee characteristics and resettlement sites.

The algorithm was tested on historical registry data from two countries with different assignment regimes and refugee populations, the United States and Switzerland. Our approach led to gains of roughly 40 to 70%, on average, in refugees’ employment outcomes relative to current assignment practices. This approach can provide governments with a practical and cost-efficient policy tool that can be immediately implemented within existing institutional structures….(More)”.

Congress Is Broken. CrowdLaw Could Help Fix It.

Curated on January 23, 2018August 3, 2018 by Stefaan Verhulst

Beth Noveck in Forbes: “The way Congress makes law is simply no longer viable. In David Schoenbrod’s recent book DC Confidential, he outlines “five tricks” politicians use to take credit in front of television cameras in order to further political party agendas while passing the blame and the buck to future generations for bad legislation. Although Congress makes the laws that govern all Americans, people also feel disenfranchised. One study concludes that “the preferences of the average American appear to have only a minuscule, near-zero, statistically non-significant impact upon public policy.” But technology offers the promise of improving both the quality and accountability of lawmaking by opening up the process to more and more diverse expertise and input from the public at every stage of the legislative process. We call such open and participatory lawmaking: “CrowdLaw.”

Moving Beyond the Ballot Box

Around the world, there are already over two dozen examples of local legislatures and national parliaments turning to the internet to improve the legitimacy and effectiveness of the laws they make; we need to do the same here if we are to begin to fix congressional dysfunction.

For example, Finland’s Citizen’s Initiative Act at the national level, like Madrid’s Decide initiative at the local level, allows any member of the public with the requisite signatures to propose new legislation, meaning that not only interest groups and politicians get to set the agenda for lawmaking.

In France, the Parlement & Citoyens platform allows the public to respond to a problem posed by a representative by contributing information about both causes and solutions. Relevant citizen input is then synthesized, debated, and incorporated into the resulting draft legislation. This brings greater empiricism into the legislative process through public contribution of expertise….(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.