Recent Bulletins

Alexander Agadjanian '18 publishes college honors thesis in Political Communication
Posted on: 07/08/2020

Alexander Agadjanian '18, who majored in Quantitative Social Science and Government at Dartmouth College, has published his college honors thesis in Political Communication, a peer-reviewed journal at the nexus of political science and communication studies.  In the article, titled "When Do Partisans Stop Following the Leader?", Alexander asks to what extent individuals form their political opinions in response to cues from political party elites.  The abstract of his new article and a link to the full text is below:  

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Evidence of public opinion blindly following political leader rhetoric has important implications for the scope of elite influence and normative democratic concerns. Past research, however, does not test the strength of real world leader cues amid signals that conflict with a leader’s policy message, and thus has not gauged the robustness of the “follow-the-leader” dynamic. The current study explores whether two different conflicting signals – 1) opposing intra-party Congressional elite cues and  2) negative policy information that gives compelling reasons to oppose a policy – attenuate leader influence in support of a realistic counter-stereotypical policy. A national survey experiment with two parallel partisan designs shows that individuals follow their leader to a substantial degree whether or not conflicting signals are present. Conflicting co-party elite cues do not attenuate leader influence among Republicans. For Democrats, although they weaken amid opposition, leader cues still shape mass opinion sizably. Providing substantially more information about the policy at hand does not make either partisan group much less likely to follow their leader, a finding that holds regardless of individuals’ preexisting ideology in the policy area. Results demonstrate the broad conditions under which “follow-the-leader” behavior holds and reveal a stronger nature of elite influence than previously understood. Party elites and information fail to effectively constrain the sway of prominent leaders, who have considerable latitude in positions they can take without losing mass support. To read the full article click here.

After finishing at Dartmouth, Alexander was a research associate in the MIT Election Lab for two years, working under MIT Professor Charles Stewart III. At MIT, he led the lab’s effort to collect, clean, and disseminate data from U.S elections from 1976 to 2018 across various geographic levels. This fall, Alexander will start a doctoral program in political science at the University of California, Berkeley.

Outside of his QSS thesis, Alexander has published papers in Political Behavior (on the causes of foreign public opinion toward the U.S.) and Research & Politics (on whether fact-checking information can promote politician accountability).


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QSS research on fake news in the age of COVID presented at Pre-Union
Posted on: 06/26/2020

Like so much of life in the summer of 2020, reunions at Dartmouth this year were virtual.  Even so, Dartmouth faculty have presented their research to alumni who are gathering in online forums.  The virtual Pre-Union recently heard from Vignesh Chockalingam ’20, who majored in Quantitative Social Science (QSS) and was a member of a Spring 2020 class on Experiments in Politics taught by Prof. Brendan Nyhan.  Prof. Nyhan is on the QSS Steering Committee, and his spring quarter class on experiments was cross-listed between QSS and the Department of Government.

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 This spring, Prof. Nyhan and his students carried out an experiment on the effectiveness of different approaches to correcting misinformation about COVID-19 and other health and science topics. They found little evidence that messages emphasizing a scientific consensus of the sort typically used on climate change were more effective than standard corrections. The class participants and Prof. Nyhan are currently preparing a paper for submission to a peer-reviewed journal.

 Research is a key aspect of the QSS curriculum, and the Experiments in Politics course exemplifies the program's connection between education and research. Students in Professor Costa's Fall 2018 Experiments course conducted a survey experiment examining how people evaluate politicians accused of sexual misconduct. They find evidence that partisanship, sexist attitudes, and the severity of the allegations strongly influence voter reactions to #MeToo allegations. The collaborative manuscript that was produced by the class is forthcoming in the academic journal Research & Politics.

 Vignesh completed an independent QSS research project this past winter quarter, and his project investigated the impact of hate crimes on academic achievement.  He found that hate crimes may worsen K-12 academic outcomes at the county level, especially in rural areas and during President Trump’s prominence in American politics.  Now that he has finished up at Dartmouth, Vignesh is planning on joining Bain and Company as an Associate Consultant in Boston this fall.

To see Vignesh and Professor Nyhan present their research at the Pre-Union, click here.

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Research Computing supports QSS during coronavirus pandemic
Posted on: 05/15/2020

The sudden shift to online teaching has presented numerous challenges for Dartmouth students and for Dartmouth College itself.  Research Computing, a unit within Information, Technology & Consulting (ITC) that provides advanced computing resources to the Dartmouth Community, has responded to the exigencies imposed by the pandemic by stepping up to help the Program in Quantitative Social Science (QSS).

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QSS offers its students an introductory statistics course known as QSS 15.  James Lo, a postdoctoral fellow in QSS and an assistant professor of political science at the University of Southern California, is teaching QSS 15 in Spring 2020.

QSS 15 is an introductory course in data analysis, and it uses the popular statistical computing environment RStudio.  Many QSS classes use RStudio as well, and one goal of QSS 15 is familiarize students with RStudio and introduce basic statistical programming techniques.

Under normal circumstances, students in QSS 15 are required to install RStudio on their own computers. This spring quarter, to help support the class Research Computing has operated an RStudio server for QSS 15 students. This allowed students to run RStudio in the cloud through the convenience of a web browser.

Having access to an RStudio server in an introductory data analysis course has vastly simplified teaching QSS 15. When setting up RStudio on their own computers, students confronting programming for the first time often run into difficulties; many students, for example, are not familiar with directory structures. The RStudio server set up by ITC has simplified the QSS 15 teaching process considerably by ensuring that all students in the course have access to all data files under the same directory structure. It also made it much easier for Professor Lo to diagnose computing problems when they arose. When, for example, one student in the course encountered a faulty installation of an auxiliary RStudio package, it was easy for Professor Lo to identify and fix this problem.  Once he addressed it, the solution was immediately accessible to all students in QSS 15 and shared with everyone in the course.

Bill Hamblen and Arnold Song, Senior Research Engineer and Assistant Director of the Advanced Computing Lab (ACL) of Research Computing at ITC, respectively, were instrumental in setting up the RStudio server.  According to Arnold, the ability for the ACL to quickly stand up the online RStudio environment was enhanced by the use of cloud services and the approach could be easily extended to expanded offerings for QSS and across the campus.  Once it became clear that QSS 15 needed an online solution, the QSS faculty and the ACL worked closely to quickly deliver RStudio in a manner that minimized disruption to the students' virtual learning.  Arnold writes, "This was a fruitful collaboration between QSS and the ACL that will likely continue and grow as we adjust to delivering an enhanced online learning environment."

George Morris, Associate CIO of Information, Tehcnology, and Consulting at Dartmouth College, has seen his organization involved in a variety of new initiatives since the coronavirus pandemic erupted.  According to George, "We have witnessed an acceleration of demand to infuse advanced technologies in research and teaching that began with the first wave of interest in data sciences.  Our teams have partnered with faculty and students from all over Dartmouth to quickly innovate and integrate solutions in ways we could not have anticipated before the pandemic.  It has been a terrific collaboration to ensure the Dartmouth experience is carried over online.”

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QSS Honors Thesis presentation schedule 2020
Posted on: 05/11/2020

This year, eight students majoring in the Program in Quantitative Social Science are completing Honors Theses.  Each QSS thesis must be publicly presented, and the schedule for presentations, along with Zoom links, is below.

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Monday, May 18, 2020

3:00 – 4:30 - Kevin Hu, Oscillating Replicator Dynamics with Attractor Arcs: A Game-Theoretical Exploration of Technology, Policy and Market Influences on Gig Economy Labor Strategies (Fu/Sirianni)

Tuesday, May 19, 2020

1:30 – 3:00 – Jenna Salvay, Can student activists differentiate themselves from other climate change communicators? A study on the role of messaging and messengers in the era of climate change (Howarth, Wu)

3:30 – 5:00 – Sunny Drescher, The Effects of Gender Cues on Support for Policy (Horiuchi, Wu)

Wednesday, May 20, 2020

9:00 – 10:30 – Grace Sherrill, What impacts support for public long-term care and its beneficiaries in the U.S.? (Lacy, Wu)

12:00 – 1:30 - Sarishka Desai, Variation in Opioid Prescription Response to Physician Targeted-Marketing (Herron/Skinner, Wu)

Friday, May 22, 2020

11:00 - 12:30 – Kate Shiber, Not-So-Fairways? The Impact of Golf Course Water Run-Off on Local Cancer Rates (Chipman, Renshaw)

2:00 – 3:30 – Aidan Sheinberg, Building Blocks of Opportunity? The Effect of Low-Income Housing Tax Credits on Intergenerational Mobility (Houle, Wu)

Monday, June 1, 2020

4:30 – 6:00 – Andrea Sedlacek, Interactions of Structure and Culture in Collaborative Groups (Rogers, Wu)

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QSS and biology major Jenny Chen publishes in The Lancet Digital Health
Posted on: 05/07/2020

Jenny Chen ’21, who is majoring in Quantitative Social Science (QSS) and Biology, has been working at the Fogarty International Center, a unit in the National Institutes of Health, since January.  At the Fogarty Center, Jenny has been involved with a variety of COVID-19 related projects, including exploring crowdsourced data from a Chinese physician website, looking at excess mortality across the United States, and predicting the outbreak of COVID-19 in places like South Africa and Pakistan. Jenny has drawn heavily on her experiences in QSS 17 Data Visualization, a course she took at Dartmouth in Summer 2019.  QSS 17, one of the core classes in the QSS curriculum, is an R-based computing course that focuses on data cleaning, manipulation, and visualization.

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As a member of the Fogarty Center’s Division of International Epidemiology and Population Studies, Jenny has recently published an article in The Lancet Digital Health titled, “Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study,” and co-authored with a senior research scientist and postdoctoral fellow. This article revealed important demographic information for 288 COVID-19 patients diagnosed in January as well as hospitalization and reporting lags by location. 

Jenny is currently working with her co-authors at the Fogarty Center and participating in their collaborations with The Washington Post and other countries’ COVID-19 surveillances system. She will continue interning at Fogarty until the end of the summer and hopes to expand on her NIH research as part of her QSS culminating project. After graduation, Jenny will be attending the Icahn School of Medicine in New York City.


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Professor Brendan Nyhan on “Social Media, Scientific Uncertainty, and Political Polarization—COVID 19’s Misinformation Storm”
Posted on: 05/04/2020

Brendan Nyhan, Professor of Government and member of the Steering Committee of the Program in Quantitative Social Science (QSS), recently spoke with Dr. Colleen Barry, chair of the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health on the “Public Health on Call” podcast. In the podcast, which is produced by the Bloomberg School, Professor Nyhan discussed his research on the politics of misinformation and how his work informs our understanding of both the human cost of misinformation during the coronavirus epidemic and the extent to which social media and politics are affecting our view of COVID-19.

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At Dartmouth College, Professor Nyhan teaches a course on experiments in politics.  This spring quarter, students in GOVT 83.21/QSS 30.03 are currently working under Nyhan’s supervision to design, field, and analyze an experimental study of COVID-19 misformation and misperceptions. To listen to the podcast episode on which Professor Nyhan was featured, click here for the Johns Hopkins podcast “Public Health on Call.”

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QSS Faculty on how to calculate infection and fatality rates of the coronavirus in the U.S.
Posted on: 04/20/2020

When it comes to the coronavirus, one thing that is certain is that there are a lot of unknowns.  Two fundamental questions about the COVID 19 pandemic remain – how many people are infected with the virus in the United States, and how many people are dying because of it? Michael Herron, chair of the Program in Quantitative Social Science and Professor of Government, and Daniel Rockmore, Associate Dean for the Sciences and Professor of Mathematics and Computer Science, suggest that the approaches we use for political polling an help answer these questions.

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If we had unlimited resources, it would be easy to find the answers to them. We could simply test every American for the virus and from the results we would be able to know definitively what the rates of infection and death are. But, as most people know, we do not have unlimited resources for testing for the virus. Given the limited resources available to us, the CDC has suggested limiting testing to patients that exhibit symptoms. The selective nature of this type of testing creates biases that make it impossible to know the rate of infection and case fatality rate. Herron and Rockmore suggest that the problem is not in the number of tests, but rather who is being tested. They offer a simple solution to this problem: test randomly. Random selection in coronavirus testing is being used in Munich and there is planning for this in the state of Ohio as well. To view the full article by Herron and Rockmore click here.

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QSS thesis research during the Coronavirus Pandemic
Posted on: 04/13/2020

One of the key components of the Program in Quantitative Social Science (QSS) at Dartmouth College is student research.  All QSS students complete research projects during their last year on campus, either a one-quarter project or an honors thesis.  This year, eight students are writing theses, projects which take an entire academic year to complete.  Each QSS thesis is publicly presented and defended before a committee consisting of the QSS Director of Undergraduate Research, the main advisor of each student, and a second reader.  QSS thesis defenses are open to the Dartmouth community at large.

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QSS theses are guided by Professors Robert Cooper and Ahra Wu. Professor Cooper has been at Dartmouth for two years and is the current QSS Director of Undergraduate Research.  Professor Cooper teaches a regular QSS course on data visualization (QSS 17), and his research focuses on American political institutions. Professor Wu, who recently finished her doctorate at Rice University and also has a masters degree in statistics, is a visiting professor who teaches and researches quantitative methods and comparative politics, focusing on international conflict.

Spring 2020 at Dartmouth has been disrupted by the coronavirus pandemic. During this time, QSS students continue to work hard on their honors theses even under trying conditions. Grace Sherrill, one of the eight QSS majors working on an honors thesis this academic year, wrote of her remote learning experience so far, “While it took some time to adjust to the new work environment, I’m finding that working from home has given me a valuable new perspective on my thesis. Describing my project to my parents has made my ideas clearer and improved my writing. In our thesis course in the fall, we learned that the best papers are intelligible to people with little background on the subject we are studying. Translating the results of my analyses into less technical terms for my parents has allowed me to better articulate what I’m studying and why the results are important. Though I miss seeing my QSS peers and professors on campus, frequent Zoom calls have allowed me to maintain a dialogue and receive important feedback. I’m looking forward to presenting my results over Zoom in the coming months!”

Each QSS thesis has a formal advisor, and these advisors are key to the QSS thesis program. Advisors provide regular guidance relative to their areas of expertise and encourage students during the yearlong arc of their original research projects. Good relationships between advisors and students provide a foundation to successful honors theses.

Sunny Drescher, another QSS student working on a thesis, writes “I feel lucky that much of my thesis work has been unhindered by working remotely. My advisor, Professor Horiuchi, has been available to meet frequently via Zoom and to give me feedback via email. I have been working on a survey experiment to try to understand how women’s support for various policies impacts voters’ support for those policies. A lot of gender and politics research focuses on women’s viability as political candidates, but there has been less work done on the extent to which gender impacts voters’ perceptions of and support for policy. This project uses survey experiments to estimate the impacts of different gender-related cues on respondents’ support for various policy issues. While the Covid pandemic has not affected my ability to complete my thesis (so far), the crisis influenced the policy issues I was testing; I intended to use paid family leave as one of the issues, but since that type of policy has become much more practically salient in the past weeks, I had to exclude it from my survey. This research aims to provide insight into the extent to which women’s support influences voters’ opinions on policy issues, and I look forward to completing it with (hopefully) no additional pandemic-related issues.”

As to the challenges for working remotely, Kevin Hu writes, “For me, this had made it challenging to communicate with professors and actively receive feedback on my thesis work. My thesis advisor, Professor Feng Fu, challenged me to prepare my thesis manuscript in parallel to an abridged version for potential journal submission. We discussed expectations and goals during the winter term, and I've been doing my best to execute remotely. I plan to meet with him over Zoom next week to do a walkthrough on both drafts. My thesis is a game-theoretical exploration of market, technology and policy influences on labor strategies in the gig economy. In recent years, scholars have extensively studied the gig economy, producing academic works that address labor preferences, policy design, the role of technology and wide-ranging socioeconomic implications. Applying methods from evolutionary game theory, we consolidate several of these areas of inquiry into a comprehensive model. We extend the replicator equation to model oscillating dynamics in two-player asymmetric bi-matrix games with time-evolving environments, introducing concepts of the attractor arc, driven oscillation, trapping zone and escape.”

This year, QSS students are writing honors theses on wide-ranging topics.  These range from public attitudes on long-term healthcare, labor-market relations and outcomes in the gig economy, public policy changes and intergenerational socioeconomic mobility, luxury property environmental exemptions and cancer rates, pharmacological advertising and prescription rates, and the effects of gender on public attitudes and voting preferences. Below is the list of current QSS theses students, their advisors, and tentative thesis titles.


Sarishka Desai.  Advisors: Michael Herron (Government) and Jonathan Skinner (Economics). Variation in Opioid Prescription Response to Physician Targeted-Marketing

Sunny Drescher. Advisor: Yusaku Horiuchi (Government). The Effects of Gender Cues on Support for Policy

Kevin Hu. Advisor: Feng Fu (Mathematics). Oscillating Replicator Dynamics with Attractor Arcs: A Game-Theoretical Exploration of Technology, Policy and Market Influences on Gig Economy Labor Strategies

Jenna Salvay. Advisor: Richard Howarth (Environmental Studies). Can student activists differentiate themselves from other climate change communicators?: A study on the role of messaging and messengers in the era of climate change

Andrea Sedlacek.  Advisor: Kimberly Rogers (Sociology). Interactions of Structure and Culture in Collaborative Groups

Aidan Sheinberg.  Advisor: Jason Houle (Sociology). The Effect of Low-Income Housing Tax Credits on Intergenerational Mobility

Grace Sherrill. Advisor:  Dean Lacy (Government). What impacts support for public long-term care and its beneficiaries in the U.S.?

Kathryn Shiber. Advisor: Carl Renshaw (Earth Sciences). Not-So-Fairways? The Impact of Golf Course Water Run-Off on Local Cancer Rates

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QSS offers course in Quantitative Literary Criticism
Posted on: 03/11/2020

The Program in Quantitative Social Science at Dartmouth College offers students the opportunity to combine modern methodological training with enduring questions in the liberal arts. This is exemplified by Neukom Fellow Joseph Dexter's course in Quantitative Literary Criticism. This course, cross-listed in QSS and the Department of Classics, is described as follows:

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Digitization of vast numbers of texts and rapid advances in computational methods are enabling new forms of criticism in all areas of literary study. Classics was an early adopter of digital technologies, and computation is now pervasive throughout the field, as illustrated by flagship projects such as the Perseus Digital Library. Beyond the familiar examples of digitized texts and simple word searches, scholars and students also benefit from an ever-growing array of sophisticated quantitative tools, and from increasing engagement with diverse technical disciplines – natural language processing, data science, even bioinformatics. Through a survey of recent research at the intersection of Latin literature and the digital humanities, this course will introduce you to the state of the art in quantitative literary criticism. To ground our methodological investigations, we will explore a diverse selection of Latin poetry, including epic (Vergil, Lucan, and Catullus), elegy (Catullus), and comedy (Plautus), and sample some less famous later authors, such as Paul the Deacon and Vitalis of Blois, who were influenced by classical antecedents. At each turn, we will examine the interplay between traditional (close reading, philology, theory) and data-driven analyses of Latin literature and consider how quantitative methods can support humanistic inquiry. Along the way, you will gain hands-on experience with powerful computational tools and be introduced to now ubiquitous critical approaches, such as intertextuality and reception studies. Assigned readings will be in English translation using bilingual Latin-English editions; in addition to reading all of the English, students with Latin will be responsible for understanding and translating “micro samples” of the original texts.

Joseph Dexter received his doctorate in Systems Biology from Harvard University after having studied chemistry as an undergraduate at Princeton University Dr. Dexter is one of the founders of the Quantitative Criticism Lab, and his current research focuses on the use of computational methods from natural language processing, machine learning, and bioinformatics to understand large-scale changes in literature and culture.

Dr. Dexter taught Quantitative Literary Criticism last spring. During the term, students had the opportunity to participate in the Digital Humanities Beyond Modern English  conference, which brought 14 experts on text analysis for premodern languages to campus. Teams of students also completed independent research projects of their own design, including application of the Tesserae search tool to trace patterns of influence in Latin literature and contributing to the open-source Classical Language Toolkit.


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QSS faculty member on “Mathematical Humanities”
Posted on: 02/25/2020

Assistant Professor of Mathematics Feng Fu, who teaches Evolutionary Game Theory in the Program in Quantitative Social Science, was recently profiled in Dartmouth News. Professor Fu received his doctorate  in Dynamics and Control from Peking University in 2010 and thereafter completed a postdoctoral fellowship at ETH Zurich thereafter.  Professor Fu’s present research is focused mainly on stochastic modeling of cancer evolution and infectious diseases as well as on the emergence of drug resistance, with particular respects to cancer and HIV treatments.  Professor Fu recently published an article on social contagion with Herbert Chang, a 2018 graduate of Dartmouth College who majored in Quantitative Social Science.