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Grumpy Voters Want Better Stories. Not Statistics

In the final count, Trump collected 312 electoral votes to 226 for Democratic nominee Kamala Harris. While some votes are still being counted, the broad trends that won the election for Trump are also coming into focus. Echoing public opinion scholars, Duncan Watts of the University of Pennsylvania’s Annenberg School for Communication, author of Everything Is Obvious Once You Know the Answer, believes that Trump benefited from a broad anti-incumbent trend seen in elections worldwide; that sentiment swung enough undecided voters to his tally to win him the swing states needed for victory.

Commonsensicality: A New Platform to Measure Your Common Sense

Most of us believe that we possess common sense; however, we find it challenging to articulate which of our beliefs are commonsensical or how “common” we think they are. Now, the CSSLab invites participants to measure their own level of common sense by taking a survey on a new platform, The common sense project.
Since its launch, the project has received significant media attention; it was recently featured in The Independent, The Guardian, and New Scientist, attracting over 100,000 visitors to the platform just this past week.

CSSLab 2024 End-of-Summer Research Seminar Recap

On August 2nd, ten undergraduate and Master’s students showcased their research at the third annual Student Research Mini-Conference, which featured presentations from all four major research groups at the Computational Social Science Lab (CSSLab) at Penn: PennMAP, COVID-Philadelphia/Human Mobility, Group Dynamics, and Common Sense. Here are the highlights from this conference: 

CSSLab Establishes Virtual Deliberation Lab to Reduce Affective Polarization

When a Republican and a Democrat sit down to discuss gun control, how is it going to go? Conversations between Republicans and Democrats can be either productive or polarizing and social scientists want to understand what makes conversations between people from competing social groups succeed, as positive conversations have proven to be one of the most effective ways to reduce intergroup conflict. However, when conversations go poorly, they can instead increase polarization and reinforce negative biases.

Accelerating the Path to a Master’s Degree

As a computer science major at Penn Engineering, Mahika Calyanakoti ’26 enjoyed her courses in data science, math, and machine learning. So when she decided to pursue an accelerated master’s degree, she chose Penn Engineering’s data science program.

“A lot of computer science undergrads go into the accelerated program in computer science, but I wanted a little more variety in my studies,” she says. “While the CIS master’s is a great program, I felt the Data Science master’s better suited my desire to broaden my academic horizons.”

The mechanics of collaboration

Like many clichés, the origins of the common mantra “Teamwork makes the dream work” is rooted in a shared experience.

For Xinlan Emily Hu, a fourth-year Ph.D. student at Wharton, that is, however, more than just a catchy saying. It is the foundation of her research into the science of teamwork. As she puts it, “The magic of a successful team isn’t just in having the right people; it’s in how those people interact and communicate.”

University of Pennsylvania Launches Penn Center on Media, Technology, and Democracy

The University of Pennsylvania today announced $10 million in funding dedicated to its new Center for Media, Technology, and Democracy. The Center will be housed in the School of Engineering and Applied Science (Penn Engineering) and will operate in partnership with five other schools at Penn.

The Center will benefit from a five-year, $5 million investment from the John S. and James L. Knight Foundation as well as an additional $5 million in combined resources from Penn Engineering, Penn Arts & Sciences, the Annenberg School for Communication, the Wharton School, Penn Carey Law, and the School of Social Policy & Practice.

Detecting Media Bias

When Duncan Watts and his colleagues at Penn’s Computational Social Science Lab began work in January on a new tool that uses artificial intelligence to analyze news articles in the mainstream media, they aimed to release it before the presidential debate on June 27.

“We built the whole thing from scratch in six months—which I’ve never experienced anything like in my academic career,” says Watts, the Stevens University Professor at the Annenberg School for Communication and the director of the Computational Social Science Lab (CSSLab). “It was a huge project, and a lot of people worked relentlessly to get it up.”

The Team Communication Toolkit: Emily Hu’s Award-Winning Project

Emily Hu, a fourth year Wharton Operations, Information, and Decisions PhD student at the Computational Social Science Lab (CSSLab), has just launched her award-winning Team Communication Toolkit at the Academy of Management Conference on August 12 in Chicago. This toolkit allows researchers to analyze text-based communication data among groups and teams by providing over a hundred research-backed conversational features, eliminating the need to compute these features from scratch.

Overcoming the Challenges of GPS Mobility Data in Epidemic Modeling

Epidemic modeling is a framework for evaluating the location and timing of disease transmission events, and is a part of the larger field of human mobility science. The COVID-19 pandemic put existing epidemic models to the test, with many institutions and corporations employing models that utilized smartphone location data to measure human-to-human interactions and better understand potential transmissions and social distancing.

Duncan Watts and CSSLab’s New Media Bias Detector

The 2024 U.S. presidential debates kicked off June 27, with President Joe Biden and former President Donald Trump sharing the stage for the first time in four years. Duncan Watts, a computational social scientist from the University of Pennsylvania, considers this an ideal moment to test a tool his lab has been developing during the last six months: the Media Bias Detector.

“The debates offer a real-time, high-stakes environment to observe and analyze how media outlets present and potentially skew the same event,” says Watts, a Penn Integrates Knowledge Professor with appointments in the Annenberg School for Communication, School of Engineering and Applied Science, and Wharton School. “We wanted to equip regular people with a powerful, useful resource to better understand how major events, like this election, are being reported on.”

What Public Discourse Gets Wrong About Misinformation Online

Researchers at the Computational Social Science Lab (CSSLab) at the University of Pennsylvania, led by Stevens University Professor Duncan Watts, study Americans’ news consumption. In a new article in Nature, Watts, along with David Rothschild of Microsoft Research (Wharton Ph.D. ‘11 and PI in the CSSLab), Ceren Budak of the University of Michigan, Brendan Nyhan of Dartmouth College, and Annenberg alumnus Emily Thorson (Ph.D. ’13) of Syracuse University, review years of behavioral science research on exposure to false and radical content online and find that exposure to harmful and false information on social media is minimal to all but the most extreme people, despite a media narrative that claims the opposite.

Mapping Media Bias: How AI Powers the Computational Social Science Lab’s Media Bias Detector

Every day, American news outlets collectively publish thousands of articles. In 2016, according to The Atlantic, The Washington Post published 500 pieces of content per day; The New York Times and The Wall Street Journal more than 200. “We’re all consumers of the media,” says Duncan Watts, Stevens University Professor in Computer and Information Science. “We’re all influenced by what we consume there, and by what we do not consume there.”

Mapping How People Get Their (Political) News

New data visualizations from the Computational Social Science Lab show how Americans consume news. ith political polarization in the American public at a record high, determining where Americans get their political news is crucial to making sense...

The CSSLab Launches News Consumption Dashboard

The Computational Social Sciences Lab’s (CSSLab) new dashboard, Mapping the (Political) Information Ecosystem, is a set of four data visualizations that highlight Americans’ media consumption habits, with a focus on echo chambers and the news. This is the second of a series of dashboards launched by the CSSLab, as part of its PennMAP (Penn Media Accountability) project, and focuses on expanding knowledge on the media by translating research papers into interactive, digestible content.

Homa Hosseinmardi and Sam Wolken Speak at Annenberg Workshop

Homa Hosseinmardi and Sam Wolken of the Computational Social Science Lab (CSSLab) were recently invited to speak at the Political and Information Networks Workshop on April 25-26. This workshop was organized by the Center for Information Networks and Democracy (CIND), a new lab under the Annenberg School of Communication. CIND studies how communication networks in the digital era play a role in democratic processes, and its research areas include Information Ecosystems and Political Segregation (or Partisan Segregation).

Joe Biden’s (but not Donald Trump’s) age: A case study in the New York Times’ inconsistent narrative selection and framing

On the weekend of March 2-3, 2024, the landing page of the New York Times was dominated by coverage of their poll showing voter concern over President Biden’s age. There was a lot of concern among Democrats about the methods of the poll, especially around the low response rate and leading questions. But as a team of researchers who study both survey methods and mainstream media, we are not surprised that people are telling pollsters they are worried about Biden’s age. Why wouldn’t they? The mainstream media has been telling them to be worried about precisely this issue for months.

Hyperpartisan consumption on YouTube is shaped more by user preferences than the algorithm

Given the sheer amount of content produced every day on a platform as large as YouTube, which hosts over 14 billion videos, the need for some sort of algorithmic curation is inevitable. As YouTube has attracted millions of views on partisan videos of a conspiratorial or radical nature, observers speculate that the platform’s algorithm unintentionally radicalizes its users by recommending hyperpartisan content based on their viewing history.

But is the algorithm the primary force driving these consumption patterns, or is something else at play?

The YouTube Algorithm Isn’t Radicalizing People

About a quarter of Americans get their news on YouTube. With its billions of users and hours upon hours of content, YouTube is one the largest online media platforms in the world.

In recent years, there has been a popular narrative in the media that videos from highly partisan, conspiracy theory-driven YouTube channels radicalize young Americans and that YouTube’s recommendation algorithm leads users down a path of increasingly radical content.

New Insights on Common Sense Take the Spotlight on Canadian Radio

Mark E. Whiting was featured on Quirks and Quarks, a science and technology podcast on CBC (Canadian Broadcasting Corporation) radio. The host, Bob McDonald, is a renowned Canadian science journalist who interviewed Whiting on his recent milestone. Their conversation, “Common sense is not that common, but it is widely distributed,” was aired on January 19, 2024.

The commonalities of common sense

Throughout human history, survival and the formation of complex societies have heavily depended on knowledge. Equally crucial are the assumptions about what others perceive as true or false, namely common sense. This is evident in everyday situations like adhering to road rules: Pedestrians naturally avoid walking into traffic, while drivers refrain from driving on sidewalks to bypass congestion.

Commonsensicality: A Novel Approach to Thinking about Common Sense and Measuring it

In general we believe that we possess common sense to a certain extent, but have you ever wondered if what you perceive to be common sense is also considered common sense to others?
In other words, is common sense actually common?

The answer remains elusive in large part due to a lack of empirical evidence. To address this problem, CSSLab Senior Computational Social Scientist Mark E. Whiting and CSSLab Founder and Director Duncan J. Watts introduce an analytical framework for quantifying common sense in their paper titled: “A framework for quantifying individual and collective common sense.”

Warped Front Pages

Seven years ago, in the wake of the 2016 presidential election, media analysts rushed to explain Donald Trump’s victory. Misinformation was to blame, the theory went, fueled by Russian agents and carried on social networks. But as researchers, we wondered if fascination and fear over “fake news” had led people to underestimate the influence of traditional journalism outlets. After all, mainstream news organizations remain an important part of the media ecosystem—they’re widely read and watched; they help set the agenda, including on social networks.

Mapping the Murky Waters: The Promise of Integrative Experiment Design

My PhD journey began with a clear vision: to unravel the interplay between social network structures and their collective outcomes. I was particularly interested in the collective intelligence arising in those structures. With several projects already underway on this topic, I felt prepared. Perhaps optimistically, or some might think naively, I chose to tackle the literature review of my dissertation —often considered the “easy part”— during the first year of my PhD. always been interested in how people think, something that drew him to study literature as an undergraduate, and, now, to investigate the intersection between public opinion, local news, and politics. 

Are experimental designs one-size-fits-all? Or should they be modified to encapsulate the complexity of human behavior?

In the social and behavioral sciences, a theory provides a generalizable explanation that holds under a variety of specific conditions, and experiments are conducted to verify hypotheses which are derived from the theory. This process has become the dominant methodology under which scientific development occurs one experiment at a time, also known as the one-at-a-time approach.

Researcher Spotlight: Jorge Barreras Cortes

Having just earned his Ph.D. in applied math in December, Jorge “Paco” Barreras Cortes kicks off 2023 as a fully fledged post-doctoral researcher at the CSSLab. He has driven the Lab’s work on epidemic modeling since 2020, grappling with the types of data, machine learning, and network science quandaries that underpin the toughest challenges in the field. Read on to learn more about his research journey in this month’s Researcher Spotlight.

Call for Abstracts opens for IC²S² 2023

Abstract submissions are now open for IC²S² 2023, the premier conference for interdisciplinary researchers interested in using computational and data-intensive methods to address societally relevant problems.

Emma Arsekin expands role as Senior Communications Specialist

As 2022 draws to a close, we celebrate Emma Arsekin, who will be continuing her work at the CSSLab in the new role of Senior Communications Specialist.With 2023 promising groundbreaking new research outputs, the CSSLab is excited to draw from Emma Arsekin's...

Researcher Spotlight: Coen Needell

As of August 2022, the CSSLab is excited to welcome Coen Needell to the team as a pre-doctoral researcher. In this Researcher Spotlight, he shares about his pathway through the field of CSS, his role in the Penn Media Accountability Project (PennMAP), and how he’s poised to contribute in the year ahead.

Ph.D. Student Spotlight: Linnea Gandhi

Kicking off our Ph.D. Student Spotlight series, Summer 2022 features Linnea Gandhi, a rising third-year Ph.D. student taking the lead in the CSSLab’s work on enabling cumulative science.

Researcher Spotlight: James Houghton

As a key figure in the CSSLab’s work on high-throughput virtual lab experiments, post-doctoral researcher James Houghton aims to refocus social science around large-scale, data-driven insights. In this researcher spotlight, he shares about his path to computational social science research, his work at the CSSLab, and the exciting future for his most recent project on small-group deliberation.

End-of-Year Check-In: Celebrating the CSSLab’s Students

The CSSLab’s research assistants and Ph.D. students play a vital role in advancing the Lab’s diverse research projects. As the Spring 2022 semester comes to a close, we would like to highlight and celebrate some of our students’ recent accomplishments, various pathways to the CSSLab, and exciting summer projects.

Applications open: Penn Summer Institute in Computational Social Science

The Penn Summer Institute in Computational Social Science (SICSS-Penn) is open for applications! SICSS-Penn will bring together early-career researchers and provide opportunities for networking with Computational Social Science colleagues, interdisciplinary research collaborations, and guest lectures.

Preparing student RAs for success on the tech job market

How does working at the CSSLab impact student researchers’ career goals and experiences on the job market? We asked two of the Lab’s graduate student research assistants, Keith Golden and Kailun Li, about their experiences at various stages of their job searches.

Researcher spotlight: Mark Whiting

Spearheading the CSSLab’s work on high-throughput virtual lab experiments on group dynamics, Mark Whiting is helping to define the paradigm of large-scale, data-driven social science research. In this researcher spotlight, he outlines his research trajectory and thoughts on the future of CSS.

From the Executive Corner: CSSLab’s One-Year Retrospective

On March 10th, the CSSLab celebrated one year of working to define the new field of computational social science. To mark its anniversary month, the Lab's Executive Director, Valery Yakubovich, reflects upon our mission to adapt the core principles of CSS research to...

Call for Abstracts for IC²S² 2022

The 8th International Conference on Computational Social Science (IC²S²) solicits submissions of ongoing research, including (a) work that advances methods and approaches for computational social science, (b) data-driven work that describes and discovers social,...

What Big Data Reveals About Online Extremism

Originally published by the Annenberg School for Communication PHILADELPHIA, November 22, 2021 — Homa Hosseinmardi and her colleagues at Penn’s Computational Social Science Lab studied browsing data from 300,000 Americans to gain insights into how online...

Researcher spotlight: Homa Hosseinmardi

As the lead researcher on the Penn Media Accountability Project (PennMAP), Homa Hosseinmardi tackles questions of online political radicalization and misbehavior using large-scale data. In this month's researcher spotlight, she shares about her experience navigating...

Building the plane while flying it: How COVID shaped the CSSLab

As if coordinating across three largely autonomous schools were not difficult enough, the COVID-19 pandemic forced researchers at the CSSLab to fundamentally rethink how to collaborate. Director Duncan Watts took on the challenge of building a research lab amidst this...

Facebook shows that even “big data” can hide big bias

With private companies increasingly controlling the production and consumption of information on their platforms, their data on user habits has grown especially valuable to researchers. However, these data rarely provide a complete picture of media consumption, since...

Nature: Special issue explores computational social science

Nature's special issue on computational social science is now available in digital format. The issue features the perspective piece “Integrating explanation and prediction in computational social science,” co-authored by Lab Director Duncan Watts. Read the full issue...

Upcoming: NetSci Computational Social Science Panel

On July 2nd, 10-12 EST, Nature editors Mary Elizabeth Sutherland and Federico Levi will host a virtual round table on Computational Social Science as part of the Networks 2021 conference. The speakers, including CSSLab Director Duncan Watts, have contributed to an...

Upcoming: IC2S2 Conference on Computational Social Science

The 7th International Conference on Computational Social Science (IC2S2), organized by EHT Zurich, will take place online July 27-31. The conference brings together researchers from different disciplines interested in using computational and data-intensive methods to...

Measuring the Narrative of the Covid-19 Pandemic

New Research Project: The Analytics at Wharton Initiative awarded the CSS Lab a research grant for the project "Measuring the Narratives of the COVID-19 Pandemic." The goal of this project is to deepen our understanding of the COVID-19 pandemic—specifically, the...

The science of fake news

Co-authors David Rothschild and Lab Director Duncan Watts discuss extant social and computer science research regarding the belief in and spread of fake news. They focus on unanswered scientific questions raised by the proliferation of fake news' most recent,...

Rebuilding legitimacy in a post-truth age

Lab Director Duncan Watts and co-author David Rothschild discuss the challenges of a post-truth age, in which evidence, scientific understanding, or mere logical consistency have grown increasingly irrelevant to political argumentation. They argue that, while the...

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