Female Scientists React Before—and After—NASA’s All-Women Spacewalk Was Canceled

Until a space suit snag, BU space researchers were thrilled about the would-be historic milestone

Big Data, Big Impact

How Our Clicks Are Shaping Elections

If you think data science played a huge role in the 2016 presidential election, wait until 2020.

A generation ago, the internet changed everything. Today, data science is proving just as revolutionary. Fueled by the abundance of personal information on the internet—yours, ours, everyone’s—data science is making business smarter, healthcare more efficient, technology easier, and sports more fun to watch (and play). But it’s also made all of us more vulnerable. This article, the second in a five-story series, comes as Boston University is investing aggressively into the world of big data, and is poised to build a 17-story Data Sciences Center on Commonwealth Avenue that will house its mathematics and statistics and computer science departments. As BU President Robert A. Brown said: “This is the science that’s going to change the way we behave, driving our behavior for the next 50 or 100 years.”

In countries around the world, political events—from local town council votes all the way up to presidential elections—are being influenced, analyzed, and charted with help from data science, and specifically, machine learning. To understand just how quickly, and dramatically, data can upend the universe, look no further than the 2016 US presidential election. The data science firm Cambridge Analytica, hired by the Trump campaign, got its hands on data from 50 million Facebook users without their permission—including where they live, what types of advertisements would most likely appeal to them, and other personal preferences—then used big data and machine learning to micro-target voters who were deemed persuadable.

During that time, the New York Times reports, pro-Trump bots—autonomous software applications—that automatically sent targeted messages through social media generated one-quarter of all Twitter traffic about the election, and in days leading up to the election they outnumbered Clinton bots five to one.

Across the pond, Cambridge Analytica worked its magic on the Brexit campaign, with advice from Steve Bannon, who also worked for the Trump campaign. And in 2018, the company aided the reelection of Kenyan President Uhuru Kenyatta. BU’s Steven Rosenzweig, a College of Arts & Sciences assistant professor of political science, whose research has focused on African politics, says the company’s work in Kenya’s last two elections, both on behalf of President Kenyatta’s campaign, worried many people.

“Cambridge Analytica’s involvement—allegedly involving party branding, writing campaign speeches, and running a social media campaign—was a source of great controversy,” says Rosenzweig. “This was particularly true among the influential group of public intellectuals and activists known as Kenyans on Twitter or KOT. Particularly problematic were potential violations of privacy and the spread of inflammatory messages in a volatile political context with a history of violence.”

How is Cambridge Analytica doing today after influencing so many elections worldwide? After filing for bankruptcy, it shut down in 2018, amid so many political controversies and scandals.

The impact the company had may be felt for decades. However, in a larger political context, Rosenzweig thinks big data sometimes gets more attention than it deserves, at least for the moment. “So far,” he says, “I think the evidence that big data is having a substantial influence on politics is fairly limited and its impact sometimes overstated. But psychological motivations are key to people’s political decision-making, and data-driven strategies that are able to tap into those are quite likely to have a real impact.”

Data analytics played a lesser-known role in President Barack Obama’s 2008 campaign, which assigned potential voters scores based on the likelihood that they would vote, and then, if they would vote for Obama, guided by surveys taken in battleground states. And the next presidential campaign, in 2020, is already giving data science a leadership role. In February, President Trump named Brad Parscale, his former digital advisor, manager for his reelection bid.

Data science is also used as a purely observational tool, one that can reveal the workings, or failings, of some long-standing political processes. In 2018, three BU political scientists used big data to study local political participation in housing and development policy. Katherine Levine Einstein, Maxwell Palmer, and David Glick compiled a data set by coding thousands of instances of people who chose to speak about housing development at planning and zoning board meetings in 97 cities and towns in eastern Massachusetts, then matched the participants with voter and property tax data. The researchers found that speakers tended to be male, older, whiter, and more likely to be homeowners than most residents of their towns, and they overwhelmingly opposed new housing developments. In fact, two thirds of speakers opposed housing, and only 14 percent were in favor of building.

To learn more about how closely these meeting speakers represented the views of community residents, the researchers juxtaposed the opinions of meeting attendees with the vote on a statewide housing ballot referendum. Again, the views of speakers were not aligned with those of their broader communities.

That matters, the researchers say, because the dynamic contributes to the failure of towns to produce a sufficient housing supply. If local politicians hear predominantly from people opposed to a certain issue, it’s logical that they may be persuaded to vote against it, based on what they think their community wants. “Our study shows how political inequalities contribute to rising housing prices,” says Einstein, a CAS assistant professor of political science. “An unrepresentative group of white homeowners are able to take advantage of land use institutions to stop and delay the construction of new housing. Their actions help to block newcomers from accessing desirable communities.”

It also matters in theoretical terms, because the research shows that some supposedly democratic institutions that we have depended on for hundreds of years are, in fact, fundamentally undemocratic. “More broadly,” the researchers write, the study “reveals that institutions designed to enhance democratic responsiveness may have perverse consequences on participation, the views that policymakers hear, and/or outcomes.” Their study, “Who Participates in Local Government? Evidence from Meeting Minutes,” was published October 2018 in Perspectives on Politics.

Elsewhere at BU, Mark Crovella, a CAS professor of computer science, and Dino Christenson, a CAS associate professor of political science, working with researchers at other schools, used big data to predict which 2016 presidential candidate the public preferred, as well as how those preferences changed throughout the campaign and what the influencing events might have been. Crovella and Christenson analyzed the web-browsing histories of more than 100,000 Americans over the two months immediately prior to the election to pinpoint likely voter choice. Using data that was provided by Comscore, a kind of Nielsen rating of the internet, the researchers analyzed two terabytes of data, which included 70 million websites. They then correlated browsing patterns with public opinion polls.

Crovella says their methodology requires two things: web-browsing records, and an initial poll to calibrate their machine-learning component, so the machine knows what it’s looking for.

That, says Crovella, was the hard part, because while some websites are obviously biased, many are more nuanced. Also, he says, a visit to a particular site may not indicate the visitor’s political leanings. The researchers had to work backward, starting with traditional opinion polls to describe a particular leaning. “Let’s say you have a poll that shows that on a particular day 60 percent of people in a particular state were leaning Democratic,” Crovella says. “You use that to train an algorithm to look at everyone in the data set. You can get an idea of what a Democratic voter looks like in terms of website visits and you carry that forward, looking at subsequent visits and asking how the data is changing.”

The researchers’ say their new data-driven methodology is faster, and much less expensive than traditional polling, and it can zero in on small areas, like towns, and on specific political events that might influence opinions. The research, “Assessing Candidate Preference through Web Browsing,” is published in Proceedings of ACM KDD 2018, London, UK.

Crovella and Christenson’s original work turned up some interesting findings. Their study suggests, for example, that a last-minute dip in support for Hillary Clinton was not precipitated by a letter to Congress that reported that the FBI had found another batch of emails on Clinton’s email server. Instead, the research indicates that support for Clinton had already begun to decline three days before that event.

“This flies in the face of conventional wisdom,” says Christenson. “One of the things that makes social science so difficult is measurement. While polling can be pretty good at this, many polls have a hard time picking up fine-grained movements in particular locales and at particular times. With our approach, we were able to detect the shift in public opinion in close to real time.”

The two researchers, who are developing a method to accomplish the same goals with encrypted data that would improve the privacy of browsers, hope to build a web function that will make their technology available to social scientists and public opinion researchers.

“Ultimately,” says Crovella, “we’d like to provide a new kind of high-resolution microscope for use by the community, and we’d like to be able to open our system to researchers studying opinion dynamics on a wide range of topics.”

“I see this project as having the potential to provide a reliable and valid measure of public opinion that is not limited by time, money, or location, and therefore can provide unique insights into a number of substantive questions across a host of fields,” Christenson says. “The potential applications are virtually endless.”

View the original story on BU Today.

Author, Art Jahnke can be reached at jahnke@bu.edu.

BU Hosts Second Annual Hackathon for Women, Nonbinary People This Weekend

TechTogether Boston (2019) expected to draw more than 1,000 to Agganis Arena

Last year, women made up a mere 20 percent of those attending hackathons. But a student-run hackathon hosted by BU this weekend aims to change that.

Starting this afternoon, Friday, March 22, more than 1,200 high school and college students from across the country will hole up in Agganis Arena for 36 hours at TechTogether Boston (2019). The requirement to get in? Attendees must identify as female or nonbinary.

During the three-day event, hackers will solve problems like combating fake news, disaster recovery, and reducing environmental waste, among others. In addition to hacking, there will be a series of tech workshops, keynote talks, and networking opportunities with some of the more than two dozen sponsors (RedHat, Facebook, Microsoft, and Wayfair, to name a few) who donated more than $320,000 to underwrite the hackathon. Attendance is free, and in many cases, travel is reimbursed.

Winners will take home more than $19,000 in prizes, such as a Google Home, although some prizes have the potential to be worth a lot more: internships or job interviews at companies like Blue Cross Blue Shield and IBM Research, two of the sponsors. “This year, we are trying to convert the event into long-term opportunities,” says senior Fiona Whittington (COM), hackathon founder and advisor. “We want to get more women into the job pipeline, so that’s why we’re seeing more prizes that are more skill-based, rather than gift cards and things like that.”

Now in its second year, the hackathon began last year and was initially called SheHacks. This year’s event has been rebranded as TechTogether Boston to shy away from pronouns and better reflect a community that includes nonbinary individuals, Whittington says. The organizers are from several universities, among them BU, Northeastern, the University of California, Irvine, and UMass Boston.

Last year’s winners included teams that developed a social media listening tool that can display aid and rescue requests during a natural disaster, an app to support environmental sustainability by building a personal environment that illustrates the direct impact of climate change, and a smart waste receptacle that “reads” whether an item should be trashed or recycled, and then moves it to the appropriate side of the container.

Whittington’s impetus for starting her own hackathon last year was a bad experience when she attended a hackathon—her first—in New York as a sophomore. A guy came up to chat with her when she walked in alone and condescendingly asked if she had ever even coded before. “I told him to look at the coding stickers on my laptop,” she says. “I didn’t see a lot of women there, I didn’t go with anyone, and that, to me, was a reflection of the lack of community. There wasn’t a culture I could join, and I thought, more women need to be attending these events.” The result: SheHacks, in January 2018 at BU.

TechTogether Boston aims to create an inclusive environment that both introduces underrepresented people to the world of technology and mobilizes them to create projects. “Marginalized groups continue to be underrepresented as a whole,” in technology, says senior Isabelle Verhulst (Questrom), TechTogether’s chief marketing officer. “In this era of #MeToo, Time’s Up, and a general shift in the influence of women’s, trans, and nonbinary voices, we are proud to be doing our part in offering resources to the next generation of individuals who want to make a difference.”

“The general reaction from the community to our event has been incredible—the feedback, the amount of money we were able to raise,” Whittington adds.

And TechTogether Boston has expanded beyond this weekend’s event. The students’ new nonprofit, called TechTogether, provides members of its New York and Boston chapters with annual stipends, mentorship, and event planning resources.

TechTogether receives support from several University entities, among them the College of Arts & Sciences computer science department, BU Research, Information Services & Technology, the College of Engineering electrical and computer engineering department, BU Spark! at the Hariri Institute for Computing and Computational Science & Engineering, and Innovate@BU. BU is the hackathon’s host partner for the next three years and in addition to offering financial support and research, BU Spark! created PreHacks, an event that introduces high schoolers to the field of computer science and provides a how-to hackathon guide. Like many young women, BU Spark! marketing and program manager Elyse Bush didn’t have an introductory computer science program available to her in high school, she says, but if she had, she probably would have studied computer science as an undergrad. Bush works under Ziba Cranmer, BU Spark! director and event supporter.

Diversifying the the technology industry is in society’s best interest “given the myriad ways that technology impacts our lives,” says Tracy Schroeder, BU’s vice president of information services and technology. “Without diversity, technology services are built with implicit biases and gaps that can marginalize people and have unintended social and economic consequences.” And, she continues, change is hard: “It requires support structures like TechTogether to encourage trailblazers and change agents.”

TechTogether Boston (2019) will be held at Agganis Arena, 925 Commonwealth Ave., from 5 pm Friday, March 22, until 2 pm Sunday, March 24. Registration for the event is closed.

Author, Amy Laskowski can be reached at amlaskow@bu.edu.