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Holloway Wins Grant to Merge Technology, LGBTQ Health

Ian Holloway, associate professor of social welfare, has received an Avenir Award of more than $2 million from the National Institute on Drug Abuse to advance his research into health interventions for LGBTQ communities. Holloway leads a UCLA team that is developing a social media tool designed to offer highly personalized health information to prevent substance abuse and HIV infection among gay men. Under a previous grant, the researchers built a library of nearly 12,000 data points made up of text phrases and emojis that correlate with offline health behaviors. Holloway’s Avenir Award will be used to create a machine-learning system that will monitor social media interactions with participants’ consent, then send customized health reminders and other alerts via an app. The team’s goal is to develop a wide-reaching and cost-effective tool to promote public health, said Holloway, director of the Hub for Health Intervention, Policy and Practice at UCLA Luskin. The Avenir Awards, named for the French word for “future,” provide grants to early-stage researchers who propose highly innovative studies, particularly in the field of HIV and addiction.


 

Holloway on Dating Apps as a Tool for Crime

Ian Holloway, associate professor of social welfare, spoke to NBC News about a string of attacks against gay men who were targeted through the dating app Grindr. Anti-LGBTQ hate crimes rose 3 percent nationally in 2017, the story reported. In some cases, apps such as Grindr are used to identify victims who may be kidnapped, robbed, carjacked, assaulted or slain. Holloway noted that the risk is international in scope. “There are people impersonating romantic partners and friends in countries where being gay is illegal, then threatening to out the user,” he said. Experts advise app users to guard their personal information and create a safety plan. Holloway noted that LGBTQ dating platforms can have a positive impact. “Parts of the U.S. can be incredibly isolating for LGBTQ people, which is where the apps come in,” he said. “For people living in these areas or in countries where homosexuality is criminalized, apps can be a way to build community.”


 

Peterson on Changing Role of Social Media in New Generation of Politicians

Public Policy Professor Mark Peterson commented on the intersection of politics and social media in a Daily Bruin article discussing the new generation of millennial politicians. Following a historical shift in the demographics of the House of Representatives after the 2018 midterm elections, young politicians like Congresswoman Alexandria Ocasio-Cortez are incorporating their knowledge of social media navigation to engage their followers in the behind-the-scenes of politics. According to Peterson, Ocasio-Cortez’s “interactions on social media are giving a lot of people previously excluded from systems of information a look into an institution that many don’t know a lot about.” Social media engagement appears to be making politics more accessible and interesting to the American public. It remains to be determined what role social media will play in the future of politics, but Peterson said he “understands Ocasio-Cortez’s efforts to document her public service and broadcast it to the average American.”


Tapping Twitter to Understand Crowd Behavior and Protests UCLA Luskin Public Policy scholar Zachary Steinert-Threlkeld authors a how-to guide on cutting-edge research using social media data

By Stan Paul

Zachary Steinert-Threlkeld has long been fascinated by crowd dynamics, especially among those drawn to mass demonstrations. As a Ph.D. candidate in political science, Steinert-Threlkeld knew that social media generated at protests were a rich source of data — but he could find few tools to help him analyze it.

Now, in a world awash with popular uprisings and social movements — from Tahrir Square in 2011 to the Women’s March following the 2017 presidential inauguration — the assistant professor of public policy at the UCLA Luskin School of Public Affairs has used data generated by millions of posts on Twitter to learn more about crowd behavior and mass motivation.

Steinert-Threlkeld created a guide for acquiring and working with data sets culled from Twitter, which has more than 320 million global accounts generating more than half a billion messages every day.

His efforts culminated this year with the publication of “Twitter as Data,” the first guide in Cambridge University Press’ new Elements series on Quantitative and Computational Methods for Social Science. The series provides short introductions and hands-on tutorials to new and innovative research methodologies that may not yet appear in textbooks.

“When I was learning this as a graduate student, there was a lot of piecing together this information,” said Steinert-Threlkeld, who said he relied on sources such as Twitter documentation and online Q&A forums such as Stack Overflow. “I was able to do it, but it would have been a lot nicer if I had a textbook to show me the lay of the land.”

Steinert-Threlkeld, whose work combines his interest in computational social science and social networks with his research on protest and subnational conflict, said the book includes an interactive online version that allows users to click on links to download information and even sample data.

“It is differently comprehensive than a book,” Steinert-Threlkeld said. He described it as a “more interactive book experience — the first in social science that does this.”

In the book, Steinert-Threlkeld writes: “The increasing prevalence of digital communications technology — the internet and mobile phones — provides the possibility of analyzing human behavior at a level of detail previously unimaginable.” He compares this to the development of the microscope, which “facilitated the development of the germ theory of disease.”

He adds: “These tools are no more difficult to learn and use than other qualitative and quantitative methods, but they are not commonly taught to social scientists.”

To remedy this, Steinert-Threlkeld provides a systematic introduction to data sources and tools needed to benefit from them.

For example, people always want to know who’s protesting and how that influences others who might protest, Steinert-Threlkeld said. Most information has been restricted to surveys, which have limitations. “And so the researcher either gets lucky and happens to have scheduled a survey that occurs during a protest, but usually it’s after the fact.”

That is what’s exciting about using big data to study crowd behavior. “It’s like people always answering surveys,” he said. “Basically, every second you’re giving me survey data. Now we can tell in real time who’s protesting.”

One application of Twitter data is estimating crowd size, Steinert-Threlkeld said. In the past, he has had to rely on reports from organizers, police and the media to gauge the size of protests. “But I’m collecting tweets with GPS coordinates so I can say, ‘Oh, there are these many tweets or these many users from L.A. at this time or Pershing Square at this time, and explain whether that’s a reliable estimate or not of actual protesters.”

Twitter information can also be used to create data based on images shared from protests, Steinert-Threlkeld said. “The work I did before was all text based: What are people saying? Who’s saying it? When are they saying it? That sort of thing. But people share a lot of images online. They share more than they did three or four years ago. It’s really where the space is moving.”

Steinert-Threlkeld said that getting data into a form that a researcher can use requires a different skill set than designing and administering a survey. “But it’s still in some ways survey-like at the end of the day,” he said.

And “it’s fun,” he said. “Now we can tell in real time who’s protesting. We don’t know where the person lives, or their income, or their name. It’s still anonymous. We don’t know if the person who shares the image was there so we’re not incriminating anyone, but we can get a lot of information about protesters that we couldn’t before.”

In the final section of his guide, Steinert-Threlkeld writes: “These data are not a ‘revolution.’ Instead, they represent the next stage in the constant increase in data available to researchers. To stay at the forefront of data analysis, one needs to know some programming in order to interface with websites and data services, download data automatically, algorithmically clean and analyze data, and present these data in low-dimension environments. The skills are modern; the change is eternal.”

New Sources, Innovative Applications of Big Data Explored at Conference UCLA Luskin Center for Innovation researchers demonstrate how digital technology is transforming humans into sensors that generate behavioral data on an unprecedented scale

By Stan Paul

If your 2016 Thanksgiving dinner was shorter than usual, the turkey on your dining table may not have been to blame.

Who you had dinner with and their political affiliations following last year’s divisive election may have shortened the holiday get-together by about 25 minutes — or up to an hour depending on how many campaign/political messages saturated your market area. It’s all in the data.

“It’s not that conservatives and [liberals] don’t like eating Thanksgiving dinner with each other;  they don’t like eating Thanksgiving dinner together after an incredibly polarizing period,” said Keith Chen, associate professor of economics at the UCLA Anderson School of Management. Chen was among a group of scholars and data researchers who presented recent findings on Aug. 25, 2017, at a daylong conference about computational social science and digital technology hosted by the UCLA Luskin Center for Innovation.

Information gleaned from social media and from cellphone tracking data can reveal and confirm political polarization and other topics, such as poverty or protest, said researchers who gathered at the “The Future of Humans as Sensors” conference held at the UCLA Luskin School of Public Affairs.

The event brought together social scientists and data researchers to look for “ways to either extend what we can do with existing data sets or explore new sources of ‘big data,’” said Zachary Steinert-Threlkeld, assistant professor of public policy at UCLA Luskin and the leader of the program.

Steinert-Threlkeld presented his latest research, which was motivated by the Women’s March in the United States, as an example of measuring protest with new data sources that include geo-located Twitter accounts. While conducting research, Steinert-Threlkeld has observed that working with social media data has actually become more difficult of late.

“While Facebook lets you use data from profiles that are public, most people have private profiles,” Steinert-Threlkeld said. Seeing private data requires researchers to work directly with Facebook, which has become more cautious in the wake of a controversial 2014 paper, thus impacting what scholars can publish. In addition, Instagram previously provided much more data, but since 2016 it has followed the Facebook model and that data has been severely restricted despite Instagram’s norm of having public profiles, he said.

“This workshop will discuss how ‘humans as sensors’ can continue to yield productive research agendas,” Steinert-Threlkeld told conference attendees.

Talking about new and innovative ways to do this, Michael Macy, a sociologist and director of the Social Dynamics Laboratory at Cornell, began his presentation by pointing out the innate difficulties of observing human behavior and social interaction, as well as both the potential and the limitations of social media data.

“There are privacy concerns; the interactions are fleeting. You have to be right there at the time when it happens.” He added, “They’re usually behind closed doors, and the number of interactions increases exponentially with the size of the population.”

But, Macy said, new technologies in various scientific fields have opened up research opportunities that were previously inaccessible.

“We can see things that we could never see before. In fact, not only can we see things, the web sees everything and it forgets nothing.”

He tempered the potential of digital data with the fact that for the past several decades the main instrument of social science observation has been the survey, which comes with its own limitations, including unreliability when people recount their own behavior or rely on memories of past events. But, he said, “In some ways I see these social media data as being really nicely complementary with the survey. They have offsetting strengths and weaknesses.”

Macy provided examples of ways that tracking of political polarization can be done, not by looking at extreme positions on a single issue but by inferring positions on one issue by knowing the position that individuals hold on another. This can range from their choices of books on politics and science to their preferences for cars, fast food and music.

“The method seems to recover something real about political alignments … political alignment can be inferred from those purchases, and then we can look to see what else they’re purchasing,” Macy said.

“What I think we’re really looking at is not the era of explanation, at least for now … it’s the era of measurement, and what we are now able to do is to test theories that we could not test before because we can see things that we could not see before.”

The day’s presentations also included the ways in which data can be used to provide rapid policy evaluation with targeted crowds and how demographic sampling weights from Twitter data could be used to improve public opinion estimates. Data could also help fight poverty worldwide.

The world seems awash in information and data, but “most of world doesn’t live in a data-rich environment,” said presenter Joshua Blumemstock, an assistant professor at U.C. Berkeley’s School of Information and director of the school’s Data-Intensive Development Lab.

“You can use Twitter data to measure unemployment in Spain. The problem is that these methods don’t port very well in developing countries,” Blumenstock said. “There’s these big black holes in Africa for Twitter.”

Blumenstock discussed how data from billions of mobile phone calls in countries such as Rwanda could be used in conjunction with survey data to create a composite of where individuals fall on the socioeconomic spectrum. In turn, the information collected could be “aggregated up” to a much larger regional or national level.

“And when you aggregate up, you start to get things that might be conceivably useful to someone doing research or some policymaker,” such as being able to respond instantaneously to economic shocks, Blumenstock said. In addition, instead of costing millions of dollars and taking years, he said this methodology could potentially cost thousands of dollars and be conducted in weeks or months.

“For researchers like me who are interested in understanding the causes and consequences of poverty … just measuring the poverty is the first step. For people designing policy for these countries, their hands are tied if they don’t even know where poverty is,” Blumenstock explained. “It’s hard to think about how to fix it.”