Recent Bulletins

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.  

Jennifer Wu '19 presents thesis at Japanese politics workshop
Posted on: 01/20/2020

Jennifer Wu, who graduated with a degree in Quantitative Social Science from Dartmouth College in 2019, presented her undergraduate honors thesis at the inaugural meeting of the Northeast Workshop on Japanese Politics.  This workshop was organized by Professor Yusaku Horiuchi of Dartmouth's Department of Government and funded by a conference grant from the College. The speakers at, and co-organizers of, the workshop included Frances Rosenbluth  at Yale University, Christina Davis  and Daniel M. Smith at Harvard University, and Amy Catalinac at New York University.  According the Professor Horiuchi, it was one of the largest workshops ever organized specifically on Japanese politics.Jennifer is currently a pre-doctoral fellow at Stanford University, where she is supervised by Professors of Political Science Andrew Hall and Justin Grimmer.  Jennifer is currently working on a project studying Youtube and political polarization, and she is taking Stanford’s quantitative methods sequence for political science.  While at Stanford, Jennifer plans to continue researching political communication and behavior, and with Professor Horiuchi she is working on revising her QSS honors thesis for submission to an academic journal.

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QSS scholars publish article on racial inequalities in drug policy
Posted on: 12/10/2019

Three scholars associated with the Program in Quantitative Social Science at Dartmouth College recently published a paper in the Journal of Health Politics, Policy and Law. Their paper, titled "Treatment versus Punishment: Understanding Racial Inequalities in Drug Policy," analyzes racial inequalities in policy responses to the ongoing opioid crisis and the crack scare of the 1980s and 1990s. Many observers believe that policy responses to the opioid crisis are less punitive than those associated with the crack scare and that the reason is that victims of the former are (stereotypically) white. The study's authors compare policy responses to these twin health crisis and show that legislators across the United States have introduced more drug treatment-related bills during the opioid crisis than punitive bills.  This was not the case during the crack scare.  However, the study’s author show as well  that legislators seeking to response to the opioid crisis have been more responsive to white deaths than black deaths in their legislative activities. This result suggests that the recent shift toward treatment-oriented responses to the opioid crisis is driven by white victims, and it constitutes evidence that racial inequalities in American drug policy are persistent.

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The study's authors are Jin Woo Kim, Evan Morgan, and Brendan Nyhan. Kim, a post-doctoral fellow at the University of Pennsylvania, was a post-doctoral fellow in QSS during 2017-19 and is currently working on research projects on how partisans respond to new information and the effects of political rumors on public opinion. Morgan graduated from Dartmouth with a degree in QSS in June 2019 and is currently working as a data engineer at Mastercard. Nyhan is Professor of Government at Dartmouth College and serves on the QSS Steering Committee.

 

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QSS alumni work with data and each other
Posted on: 09/13/2019

Three former Dartmouth College students, Franklin Dickinson ’16, Clara Wang ’17, and Junghye Kim ’19, who studied in the Program in Quantitative Social Science, recently crossed paths as employees in the Washington, DC and Chicago offices of Civis Analytics, a data science consultancy and technology firm founded by the former chief analytics officer for Barack Obama’s re-election campaign.  Clara Wang was the first Dartmouth student to complete a minor in QSS, and Junghye Kim was a QSS major.

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These three students all took Brendan Nyhan’s Experiments in Politics seminar, which is cross-listed in QSS and Dartmouth's Department of Government.  They are also co-authors on a manuscript reporting the results of the randomized controlled trial they conducted in the class, which they hope to publish in the coming year. Clara Wang recently left Civis after two years to pursue graduate study in China after being selected as a Yenching Scholar.

The Applied Data Scientist role at Civis involves coding in R, SQL, and Python to analyze, visualize, and communicate data, with a particular focus on survey data and predictive models. On the Political team at Civis, data of interest often pertain to which races are most important when considering resource allocation, the demographics and preferences of the electorate within such races, and which messages matter most to electorates.

Civis is Franklin’s second job since graduating Dartmouth; he first worked for a year and a half as a Revenue Intelligence Analyst for a search engine marketing technology startup in Buenos Aires, Argentina.  After this job, Franklin attended a three month data science bootcamp in New York City. He distinctly credits his time learning experimental design and online surveys in Nyhan’s Experiments in Politics in preparing him for his work now.

Civis is Junghye’s first job post-graduation. She has been able to use skills she learned in her QSS classes, such as tidyverse from both Data Visualization and Race, Incarceration, and Politics; survey research techniques from Experiments in Politics and the Washington, DC, Foreign Study Program; and, machine learning concepts from Computational Text Analysis. Overall, Junghye feels fortunate to have been a part of QSS at Dartmouth and to have had the opportunity to think about social phenomena and apply quantitative skills to learn more about them-something she does daily in her job.  She is always happy to talk more about her experience in QSS and/or life at Civis and interested students should feel free to reach out at jkim2@civisanalytics.com.

 

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QSS graduate on Joe Biden's ability to attract black and racially resentful voters
Posted on: 09/09/2019

Alexander Agadjanian, a 2018 graduate of Dartmouth College's Program in Quantitative Social Science, who currently works at the MIT Election Lab, recently published an article in the Washington Post examining what's shaping candidate preferences in the Democratic presidential primary. He finds significant roles for voter prejudices, like racial resentment and sexism, in dividing Democratic voters and an interesting paradox as well: current leader and former vice president Joe Biden enjoys huge advantages among both African American voters and also among those high in anti-black prejudice. In this recent work, Agadjanian applied the data analysis and visualization skills he learned in QSS 17 Data Visualization, a course he took his third year at Dartmouth.

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Since leaving New Hampshire, Agadjanian, who double-majored in QSS and Government, has been working on election data projects at his lab at MIT. He’s also involved in numerous other research projects, including a recent academic publication with Dartmouth Professor of Government Brendan Nyhan and other seminar classmates, and a resently presented a paper at the 2019 Annual Meeting of the American Political Science Association in Washington, DC.  This paper uses cast vote records—also known as ballot logs---to study rates of ticket splitting, e.g., voting for a Democratic presidential candidate and a Repulican United States Senate candidate. More of Agadjanian's work is available on his website. In addition, Agadjanian has maintained a politics and data blog, where he puts his data analysis skills to use.

Agadjanian wrote an Honors Thesis in QSS, titled "Party Leader Influence and Conflicting Signals in Opinion Formation.” In this work, Agadjanian explores the ability of political party leaders to influence public opinion. He finds that intra-party elite division — for example, when Republicans oppose Donald Trump on policy — significantly weakens a leader’s (here, Trump’s) persuasion ability. Policy information, on the other hand, is not particularly effective in remedying blind leader adherence: partisans still mostly “follow the leader” even after they’re better informed about the policy they’re evaluating. Agadjanian currently is in the process of revising his thesis for publication, and the latest version of it can be found here.

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Professor Yusaku Horiuchi featured in Dartmouth admissions magazine
Posted on: 08/21/2019

Professor of Government and Mitsui Professor of Japanese Studies Yusaku Horiuchi is a dedicated teacher and distinguished scholar.  His deep engagement with students at Dartmouth is profiled in the August 2019 Dartmouth Admissions magazine. Professor Horiuchi serves on the Steering Committee of the Program in Quantitative Social Science (QSS), and teaches its most popular course, Data Visualization.

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Professor Horiuchi first taught Data Visualization in the winter term in 2015, and this course operates in a "flipped" fashion.  This means that the typical lecture and homework elements of a course are reversed. Students watch video lectures (and work on other materials) as homework. Then, in regular class meetings, they work on coding exercises or work on their own data visualization projects. According to Professor Horiuchi, the advantage of a flipped classroom is that students can enjoy “experiential” and “active” learning through a variety of in-class activities with rich data and examples.

This past year, Professor Horiuchi advised two QSS honors theses. According to Jennifer Wu, one of Professor Horiuchi's 2019 advisees, "Professor Horiuchi sets a high bar for his students and dedicates a great deal of time and effort to help them meet that bar. I am lucky to have been able to take his classes and work on my undergraduate thesis with him - in all of my experiences with Professor Horiuchi, he was very responsive, as well as understanding of my circumstances while still encouraging me to aim higher than the goals I set for myself."

In the past several years, Professor Horiuchi has published numerous articles with Dartmouth undergraduates.  One example is “Has Trump Damaged the U.S. Image Abroad? Decomposing the Effects of Policy Messages on Foreign Public Opinion,” a paper with Alexander Agadjanian, a class of 2018 with a QSS and Government double-major published in Political Behavior. This paper was based on the student’s independent research project supervised by Horiuchi in the Spring quarter in 2017.

According to Michael Herron, Professor of Government and Chair of QSS, Professor Horiuchi's class on Data Visualization regularly causes enrollment chaos when students sign up for classes.  "So many people want to study with Professor Horiuchi, we regularly have to open up extra sections of his Data Visualization course."

Professor of Government John Carey, who serves on the QSS Steering Committee and is presently the Associate Dean for the Social Sciences, is writing a book with Professor Horiuchi on campus diversity.  One of Professor Horiuchi's great talents, notes Professor Carey, is his ability to identify where every student is on his or her personal learning curve.  This helps Professor Horiuchi propel his students forward.  Professor Carey writes, "For students who are struggling with basic concepts, Professor Horiuchi pulls them toward mastery.  For students who have command of the material and are ambitious, Professor Horiuchi welcomes them as colleagues and finds way for them to make original contributions to research.  The amount of time and care Professor Horiuchi devotes to his communications with students is tremendous, and the results speak for themselves."

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Professor Brendan Nyhan publishes with undergrads
Posted on: 08/19/2019

Along with 15 Dartmouth College undergraduates, Professor Brendan Nyhan recently published "Counting the Pinocchios: The effect of summary fact-checking data on perceived accuracy and favorability of politicians." The article appears in the July-September 2019 issue of Research and Politics.

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"Counting the Pinocchios" was a class project from Professor Nyhan's 2016 Experiments in Politics seminar. Students in this course, which is cross-listed between Dartmouth's Program in Quantitative Social Science and Department of Government, work with Nyhan in a lab-style format to design, field, and analyze an experimental study of political misperceptions.

Professor Nyhan regularly teaches Experiments in Politics. Previously published articles from the course are, "Classified or Coverup? The Effect of Redactions on Conspiracy Theory Beliefs" and "Real Solutions for Fake News? Measuring the Effectiveness of General Warnings and Fact-Check Banners in Reducing Belief in False Stories on Social Media." Research in this seminar has been supported by Dartmouth Undergraduate Advising and Research and the Dartmouth Center for the Advancement of Learning.

Professor Nyhan serves on the QSS Steering Committee. Among the co-authors of "Counting the Pinocchios" are Alexander Agadjanian '18 (QSS / Government double major); Ray Lu '18 (QSS Minor), Annie Ma ‘17 (QSS Minor), and Clara Wang ’17 (QSS Minor).

The abstract of "Counting the Pinocchios" is as follows:

Can the media effectively hold politicians accountable for making false claims? Journalistic fact-checking assesses the accuracy of individual public statements by public officials, but less is known about whether this process effectively imposes reputational costs on misinformation-prone politicians who repeatedly make false claims. This study therefore explores the effects of exposure to summaries of fact-check ratings, a new format that presents a more comprehensive assessment of politician statement accuracy over time. Across three survey experiments, we compared the effects of negative individual statement ratings and summary fact-checking data on favorability and perceived statement accuracy of two prominent elected officials. As predicted, summary fact-checking had a greater effect on politician perceptions than individual fact-checking. Notably, we did not observe the expected pattern of motivated reasoning: co-partisans were not consistently more resistant than supporters of the opposition party. Our findings suggest that summary fact-checking is particularly effective at holding politiciansaccountable for misstatements.

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Apply for a QSS Postdoctoral Fellowship
Posted on: 07/17/2019

The Program in Quantitative Social Science (QSS) at Dartmouth College is pleased to announce that it is searching for postdoctoral fellows for the 2020-21 academic year. QSS is an interdisciplinary program that integrates modern statistical, computational, and mathematical tools with social science questions. Each fellow should be highly motivated, collegial, and able to work independently on a research agenda that is grounded in quantitative social science. Fellows should be interested in working with existing QSS faculty who have expertise in a diverse range of social science disciplines on campus (for more, see https://qss.dartmouth.edu/people).

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During the 2020-21 academic year, QSS fellows will participate in the intellectual life of the program by interacting with each other, with QSS faculty, and with undergraduate students pursuing a minor or major in QSS.  Fellows will also attend seminars and workshops and are expected to present their own research on a regular basis.  There are many postdoctoral fellows at Dartmouth College, and QSS fellows will be part of a large community on campus. Postdoctoral fellows are guaranteed one year of funding with opportunities to extend funding for an additional year.

Applications will be reviewed starting on October 25, 2019. Interested individuals can apply at the following URL: http://apply.interfolio.com/65324.  

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