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With the addition of two new professors, the study and advancement of quantitative social science at Dartmouth reaches new heights.
As an undergraduate at Dartmouth, Herbert Chang '18 became fascinated with human behavior—specifically, what separates us from artificial intelligence.
"On one spectrum, as a math major, I was simulating people as simple, rational agents with equations; on another, as a senior fellow in creative writing, I was exploring individual complexity by writing characters," Chang explains.
To bridge the two, he turned to quantitative social science—the application of statistical, computational, and mathematical tools to questions of social science. "QSS straddles these two points by testing social theories with growing complexity through quantitative analysis," Chang says.
Chang graduated from Dartmouth as a triple major in math, creative writing, and quantitative social science. He went on to earn a master's degree in artificial intelligence from the University of Edinburgh and a PhD in communication from the University of Southern California.
A computational social scientist, Chang studies social networks, online politics, and how AI shapes human relationships. His research illuminates and quantifies major influential trends, from how Instagram facilitated the 2020 Black Lives Matter movement to misinformation during the 2020 Taiwanese presidential election.
This past fall, Chang returned to his alma mater as an assistant professor of quantitative social science—and also made it onto Forbes' 2024 30 Under 30 in Science list.
A social media study he published this fall demonstrated that fans of K-Pop helped public health messaging about wearing masks go viral.
Chang is one of two new faculty in the Program in Quantitative Social Science, which launched as a major in 2015 and brings together scholars and students interested in examining social science questions through the application of statistical and mathematical tools. The program offers undergraduates a major and minor, both of which combine mathematical training with one or more of the social sciences.
Elsa Voytas, who served as a postdoc in quantitative social science at Dartmouth during the 2021-22 academic year, also returned to campus in the fall as an assistant professor. Voytas, who completed her PhD in politics and social policy at Princeton University, examines how experiencing, remembering, and confronting past violence influences contemporary political decisions.
"I apply a range of methodological techniques, including field and survey experiments, causal inference, focus groups, and interviews, to ask how societies can advance social justice and build peace," says Voytas, whose recent work includes studies of transitional justice museums and services in South America.
"With their diverse research agendas, Herbert and Elsa showcase the breadth of quantitative social science in applying modern methodologies to bring greater understanding to important issues in society," says Michael Herron, the Remsen 1943 Professor of Quantitative Social Science and program chair. "I am thrilled to welcome them back to Dartmouth."
Chang and Voytas' arrival brings the total number of full-time quantitative social science faculty to three—effectively tripling the program's core teaching faculty, who are joined by affiliate faculty from myriad departments and programs, including English and creative writing, government, and linguistics.
Data Science for a Better World
Growing up, Voytas found inspiration in Eleanor Roosevelt and the work she did to protect human rights.
"I became interested in inequality and injustice both in my community and globally," she says.
In college, Voytas traveled to Guatemala with her history professor, who was studying communities victimized by the civil conflict.
"While we were there, I became interested in governmental policies such as reparations programs, and constructing institutions of memory, and how communities felt about them," she says. "While these policies are meant to build justice and peace, I realized that there wasn't much rigorous research about whether, when, and how they were successful in achieving these goals. I try to shed light on that question in my research."
The course Voytas taught this past fall, Introduction to Data Analysis, serves as an introduction to quantitative social science and covers key concepts in designing, interpreting, evaluating, and implementing data analysis and statistical methods.
"My research and teaching touch on a lot of different disciplines, which is something QSS faculty share," Voytas says. "During my postdoc at Dartmouth, I benefited from interacting with QSS faculty and students who had diverse backgrounds and ways of seeing things. Despite our different backgrounds, we use similar methods to answer social science questions, which paves the way for productive collaborations."
Chang also draws inspiration from working with students and colleagues.
In the Modern Statistical Computing course he taught this past fall, he was excited to "learn about the social issues that students care about and develop the right tools to study them," he says.
The class covered "the foundational data science tools universal in today's Big Data ecosystem": database manipulation in Python and SQL, beginner-friendly machine learning, and social network analysis.
"I want students to become the best data scientists," Chang says, adding that his overarching goal is "to involve undergraduates in research so they can develop their projects with high standards." He's currently working with undergraduate students in his computational social science group.
Chang also frequently collaborates on research papers with experts in other disciplines, including government, computer science, and mathematics. He recently co-authored a highly publicized study with Dartmouth colleagues Dan Rockmore, Feng Fu, and Brooke Harrington, for example, on the potential impact of sanctioning Russian oligarchs' wealth managers.
Both Voytas and Chang express delight in returning to Dartmouth.
"As a postdoc, I so enjoyed the interdisciplinary research opportunities I was afforded at Dartmouth, and I can't wait to continue with those constructive and valuable partnerships," Voytas says. "I'm also excited to try cross-country skiing!"
"Dartmouth was my first home away from home in the U.S.," says Chang, who first stepped on campus as an international student from Taiwan. "So there is a sense of homecoming. Of course, what's different is I'm on the other side of the classroom, which provides me with a full view of all the people who make Dartmouth successful."