2nd Annual Conference on Politics and Computational Social Science (PaCSS)
DATE: Wednesday, August 28
LOCATION: Georgetown University
Georgetown University Hotel & Conference Center, Washington, D.C.
The data and methodologies available to social scientists have exploded with the emergence of vast archives of passive data collection, large scale online experimentation, and innovative uses of simulation. These data are of a larger magnitude and methods are of a greater computational complexity than approaches that have dominated political science for the last 50 years.
This offers the potential for rich insights into society at scale, while simultaneously introducing new ethical and infrastructural challenges. In parallel, the information and communication technologies that have driven these changes are also driving changes in politics, around the world, that require study.
In order to understand the political world, it is increasingly important to gain access to the political communication and behavior occurring online. This preconference gathering will offer a forum for political science research in this emerging space. Example relevant topics/approaches include: analysis of social media; text analysis; use of finely granular geographic data; large scale online experimentation.
Scholars from all subfields of political science are welcome, as are researchers in other relevant disciplines, such as computer science, sociology, and physics. The meeting will take place 9am-5pm on Wednesday, August 28th at Georgetown University.
Everyone who wishes to attend should apply. We welcome applications to present, discuss or simply participate. We recognize that strength comes through diversity, and actively seek, welcome, and encourage people with diverse backgrounds, experiences, and identities to apply and attend.
This will be a one day conference with a keynote by Sandra González-Bailón of the University of Pennsylvania. A wide range of subjects for presentations are welcome, including purely methodologically oriented presentations or applications thereof; synthesis/overviews of research; discussions of ethics and/or data infrastructures; and so on. Papers are not required.
PaCSS welcomes a diverse, multi-disciplinary audience with expertise in a range of subjects and methods. Thank you for helping us build a welcoming and encouraging scholarly community of respectful, cross-disciplinary exchange.
Register for the conference at our registration page. Registration is $50 before August 12, 2019 and $100 after that. Seating is limited, so please register early to ensure space. The conference includes breakfast, lunch, coffee, snacks and a reception with bar and hors d’ oeuvres.
Pew Research Center is pleased to host two parallel training workshops (see tab above, if link does not work in your browser) at their office in downtown D.C. These workshops will focus on two key areas: 1) natural language (NLP) processing techniques and their application to social science questions; and 2) deep learning techniques with applications to image analysis for social scientists. Participants will be given hands-on experience building and training models in these subject areas and will also be able to meet members of Pew Research Center’s Data Labs team. Workshops will run from 2pm to 5pm Tuesday August 27. Light snacks and coffee will be provided. Cost per participant is $25.
PACSS 2019 is sponsored by the McCourt School of Public Policy Data Science for Public Policy Program, the Office of Provost Robert Groves, Georgetown University and Sage Publishing and the Pew Research Center.
Previous Conference: 2018 PaCSS at Northeastern
Georgetown Programs: Massive Data Institute | Master of Science in Data Science for Public Policy
2nd Annual Conference on Politics and Computational Social Science (PaCSS)
Wednesday, August 28, 2019
Georgetown University Hotel and Conference Center, Washington, DC
The data and methodologies available to social scientists have exploded with the emergence of vast archives of passive data collection, large scale online experimentation, and innovative uses of simulation. These data are of a larger magnitude and methods are of a greater computational complexity than approaches that have dominated political science for the last 50 years. This offers the potential for rich insights into society at scale, while simultaneously introducing new ethical and infrastructural challenges. In parallel, the information and communication technologies that have driven these changes are also driving changes in politics, around the world, that require study. In order to understand the political world, it is increasingly important to gain access to the political communication and behavior occurring online.
Conference Program: Wednesday, August 28, 2019
(download PDF version - including speakers)
click links below for session details and locations
Continental Breakfast (Salon ABG)
Welcoming Remarks (Salon ABG)
Lunch (Salons C,F, H) & Business Meeting (Salon ABG)
Poster Sessions (see posters tab) & Reception (Sequioa Restaurant)
- Legislative communication style: linking legislators across medium and message
Rachel Blum, Miami University; Kelsey Shoud, University of South Carolina
- Target Policymaking Under the Frame of Dark Networks: Strengths, Weaknesses and Opportunities
Joseph Shaheen, George Mason University
- Failure to Communicate: Individual Reasoning Structure and Deliberative Outcomes
Sarah Shugars, Northeastern University
- Network Event History Analysis for Modeling Public Policy Adoption with Latent Diffusion Networks
Bruce Desmarais, Pennsylvania State University
- Knowledge Decays: Temporal Validity in Online Social Science
Kevin Munger, Penn State University
- Social Media Markets for Survey Research in Comparative Contexts: Facebook Users in Kenya
Leah Rosenzweig, Institute for Advanced Study in Toulouse (IAST)
- The Influencer Ecosystem in the 2018 U.S. Primaries
Yotam Shmargad, University of Arizona
- Journalists on Twitter: Self-branding, Audiences, and Involvement of Bot
Onur Varol, Northeastern University
- A Bayesian Transition Network Topic Model for Inferring Conceptual Networks
Nick Beauchamp, Northeastern University
- The Mechanics of Emergent Political Voice
Amy Magnus, Air Force Institute of Technology
- Humans and Machines Learning Together
Stuart Shulman, Texifter
- The Digital Pulpit: A Nationwide Analysis of Online Sermons
Dennis Quinn, Pew Research Center
- 311: What's Your Emergency?
Rebekah Getman, Northeastern University
- Shifting Sands: An Agent-Based Model of Mobilization Against a Central Authority
Soha Hammam, Claremont Graduate University
- Analyzing Link Sharing Across Platforms to Study Political Messaging and Ideology
Joshua Tucker, NYU
- Event Data with Images
Zachary Steinert-Threlkeld, UCLA
- The Distorting Prism of Social Media: How Online Comments Amplify Toxicity
Jin Woo Kim, Dartmouth College
- Affective Polarization in Online Uncivil Comments
Yujin Kim, University of Texas at Austin
- Nationalized news: using large-scale collections of close captions text to identify national network stories in local news broadcasts
Pavel Oleinikov, Wesleyan University
- Measuring the European public sphere across multiple languages
Maurits van der Veen, College of William & Mary
- Ideological Scaling of Political Images
Zachary Steinert-Threlkeld, UCLA
- Using Computer Vision to Capture the Collective Perception of a Neighborhood
Jeffrey Sternberg, Northeastern University
- How do Machines See Gender? Demystifying a machine vision system
Emma Remy, Pew Research Center
- Do Women Candidates “Run as Women” Online? An Automated Image and Text Analysis of Campaign Advertising on Facebook and TV
Jielu Yao, Wesleyan University & University of Iowa
- Text-Based Approaches to Analyzing Group Behavior in Conflict Setting
Margaret Foster, Duke University
- Where the money blows – Using speeches to identify the effect of Chinese foreign aid on the US-African relationship structure
Dennis Hammerschmidt, University of Mannheim
- Measuring a Threat Perception: Text Analysis of the Speech Records of the United Nations Security Council, 1994-2019
Takuto Sakamoto, University of Tokyo
- Detecting Foreign Influence Operations’ Content on Social Media
Meysam Alizadeh, Princeton University
- Systematic biases in local news search results: an audit study
Sean Fischer, University of Pennsylvania
- Can Digital Literacy Save Us from Fake News? Evidence from the U.S.
Andy Guess, Princeton University
How Does the Media Environment Affect Readership? Evidence from an App Patient-Preferred Trial in Italy
Alessandro Vecchiato, Stanford
- Online Information Seeking during the 2018 U.S. Congressional Elections
David Lazer, Northeastern University
- Automated Coding of Political Campaign Advertisement Videos: A Validation Study
Wonjoon Hwang, Harvard University
- Comparing Human and Machine Classification of Written and Video Records of Parliamentary Debates
Christopher Cochrane, University of Toronto
- How Online Propaganda Radicalizes Foreign Citizens
Tamar Mitts, Columbia University
- Mapping Extremist Networks with Visual Imagery
Rob Williams, UNC Chapel Hill
- Religiosity and Public Policy in Congress: Analyzing the partisan dimensions of legislators’ religious rhetoric
Sarah Dreier, University of Washington
- Gender Norms and Violent Behavior in a Virtual World
Eric Dunford, Georgetown University
- Ecologies of Online Contention: From Hate to Health
Nicolas Velásquez, George Washington University
- Can Celebrities Reduce Prejudice? The Effect of Mohamed Salah on Islamophobic Attitudes and Behaviors
Alexandra Siegel, Stanford University
- Downsian Convergence on Non-Policy Issues: Evidence from Campaign Manifestos at French Legislative Elections
Caroline Le Pennec, University of California, Berkeley
- The Supply and Demand of Fact v. Opinion in Presidential Tweets
Stan Oklobdzija, Claremont McKenna College
Pandering Politicians: Ideological Changes from Primary to General Elections
Ye Wang, New York University
- From Home Base to Swing States: Spatio-temporal Analysis of Political Advertising Strategies
Piotr Sapiezynski, Northeastern University
- Automated Visual Clustering: A Technique for Image Corpus Exploration and Annotation Cost Reduction
Kevin Aslett, University of Washington
- Active Learning for Probabilistic Record Linkage
Ted Enamorado, University of North Carolina at Chapel Hill
- Data-driven causal inference for applications in political economy
Daniel Malinsky, Johns Hopkins University
- A Computational Social Science Approach to Financial Regulation
Sharyn O'Halloran, Columbia University
2nd Annual Preconference on Politics and Computational Social Science (PaCSS) at the McCourt School of Public Policy, in conjunction with the Data Science for Public Policy Program<.
Wednesday, August 28, 2019, Georgetown University, Washington DC
The poster sessions will be held at Sequioa, a restaurant on the Georgetown Waterfront, from 6:00 pm to 7:30 pm. Sequioa is a 15 minute walk or 10 minute ride-share from Georgetown's campus.
- Dynamical equilibria in iterative voting games
Samuel Baltz, University of Michigan
- Character as a Network of Spreading Activation
Bob Boynton, University of Iowa
- News by Popular Demand: Ideology, Reputation, and Issue Attention in Social Media News Sharing
Ernesto Calvo, University of Maryland
- Data Science and Analytics to Explore the LGBTQ+ Experience
Kelsey Campbell, Gayta Science
- A taxonomy of Disinfo Wars
Hossein Derakhshan, MIT Media Lab
- Ideological alignment of attention clusters
Amruta Deshpande, Graphika Inc.
- Emotion and Reason in Political Language
Gloria Gennaro, Bocconi, NYU
- The Politics of Interruption in Ecuador
Analia Gomez Vidal, University of Maryland, College Park
- "I found this on Facebook/Twitter": Use of Social Media as Source
Naeemul Hassan, University of Maryland
- Understanding Coordination Patterns of Disinformation Campaigns in Seven Countries
Franziska Keller, Hong Kong University of Science and Technology
- Language and tone in human rights promotion: friends and foes in the Universal Periodic Review
Gino Pauselli, University of Pennsylvania
- Layering Access to Reentry Programs with Agent-Based Modeling (LARPing with ABM)
Dwayne Smith , George Mason University
- Simulating elections: a multi-agent system of strategic electors and strategic parties to assist election forensics
Fabricio Vasselai, University of Michigan
- Tweet for hate? Towards an assessment of the pattern of anti-sentiment towards economic migrants and refugees in Eastern and Southern Africa
Soazic Elise Wang Sonne, University of Oxford/ Max Planck Institute (MPIDR)
- A Network Theory of the Ruling Coalition
Omer Faruk Yalcin, Penn State University
- Understanding the dynamics of global climate change rhetoric through text analysis
Bi Zhao, Purdue University
- MediaWell: Tracking and Curating Research in Disinformation Studies
Jason Rhody and Adriana DiSilvestro, Social Science Research Council
Workshops at Pew
Pew Research Center is pleased to host two parallel training workshops on Tuesday August 27 at their office in downtown D.C. These workshops will focus on two key areas: 1) natural language (NLP) processing techniques and their application to social science questions; and 2) deep learning techniques with applications to image analysis for social scientists. Participants will be given hands-on experience building and training models in these subject areas and will also be able to meet members of Pew Research Center’s Data Labs team. Workshops will run from 2pm to 5pm Tuesday August 27. Light snacks and coffee will be provided. Cost per participant is $25.
Natural Language Processing (NLP)
This workshop will offer a soup-to-nuts overview of text-as-data methods for political, social, and policy applications using R, split into two sections. The first section will provide both a practical and theoretical introduction to text-as-data approaches including: how to acquire text data, how to clean and organize text data, and challenges and considerations for working with text sources in combination with other types of data. In particular, the first section will introduce dictionary-based techniques (and discuss their pitfalls and alternatives), as well as visualization strategies for summarizing corpora. The second section will focus on more advanced approaches to evaluating text data, including clustering, topic modeling, and word embeddings.
This workshop will be led by Sarah Bouchat. Bouchat is an Assistant Professor at Northwestern University, and is core faculty in the Political Science Department as well as the Institute for Complex Systems (NICO). At Northwestern, Bouchat teaches courses in machine learning, text-as-data, Bayesian statistics, and research design for social science. They completed their PhD in the Department of Political Science at the University of Wisconsin–Madison in 2017. With research interests in political methodology, comparative political economy, and authoritarian politics with a regional focus on Southeast Asia, Bouchat's research has focused on elicited priors, as well as machine learning and Bayesian statistical applications for the study of low information, authoritarian regimes like Myanmar.
As the volume and accessibility of media content has increased in recent years, computational methods for content analysis at scale have gained popularity. Until recently, these studies limited their use of computational methods to text analysis. As a result, current innovations and developments in the field of deep learning for computer vision, or automated image content analysis, remain unfamiliar and inaccessible for most social science researchers. This workshop aims to bridge this gap, by providing a brief theoretical background along with hands-on experience with deep learning for image analysis. The focus of the workshop is on feature extraction and image classification. It will be of particular interest to scholars studying social media or any domain where large numbers of images (e.g. tens of thousands or more) need to be labeled. It also serves as a useful introduction for scholars interested in studying video data. The first part of the workshop introduces deep learning and Convolutional Neural Networks (CNNs). The second part is a hands-on tutorial using Python. It will cover how to 1) use pre-trained CNNs to extract features of interest from an image (e.g. identifying particular objects), and 2) how to train CNNs to classify images into user-determined categories using labeled examples. Experience with Python will be helpful but is not required.
This workshop will be led by Nora Webb Williams. Williams is a PhD Candidate in the University of Washington Department of Political Science studying comparative politics, methods, and political economy. Her dissertation research addresses economic resilience and the long-term impacts of colonialism on social trust, with a regional focus on the former Soviet Union. She also writes about the impact of social media and images on protest mobilization, examining diverse cases such as the 2010 revolution in Kyrgyzstan and the Black Lives Matter movement in the United States. Her primary methodological interest is in images as data for social science research, with related interests in machine learning, text as data, and causal inference. Notable experiences outside of the university setting include serving as a Peace Corps volunteer in Kazakhstan and Liberia. Her work has been published or is forthcoming in Political Research Quarterly, Central Asian Survey and Nationalities Papers.
Organizing Committee Members:
Conference participants are welcome to stay at any hotels in the area. The event will be held at the Georgetown University Hotel and Conference Center. The Hotel is located on the Georgetown University campus.
Getting to Campus
If you are driving to campus, you should plan to park at the Southwest Garage located at the bottom of Kennedy Hall. You should use 3611 Canal Road NW as the address when mapping directions in GPS. It is important to note that this garage is cash only. You can find additional directions about driving to campus here and additional information about parking here. We will share additional information about transportation reimbursements at the conference.
If you are taking a taxi or ride share vehicle, it is easiest to get dropped off at the Main Gates of the University, located at the intersection of 37th and O Streets NW. The University does not allow taxis, Ubers, Lyfts, etc. on campus, so you should not use the parking garage address or any other campus location as a drop off spot.
If you are considering public transportation, the WMATA G2 Metrobus runs from Dupont Circle to the main gate of campus.
Please note that there is a major construction project on the north side of campus (Reservoir Road). We do not recommend trying to access the conference center from that direction.
In order to access wifi on campus, switch to the GuestNet wireless network. Read more about Georgetown Wifi Services.
(click to view a PDF map)
The conference is located in the Georgetown University Hotel and Conference Center, which is attached to the Leavey Center. Sample walking routes are highlighted on the map from the main gates and southwest parking garage. Please note if you enter through the far side of the Leavey Center (#39), you will need to proceed through the building until reaching the Conference Center (#40). You will not be able to drive directly to the hotel because of ongoing construction.
To find the Conference Center within the Leavey Center, please refer to this map of the building layout.
The reception will be held at Sequoia restaurant.
If you plan to walk, taxi, or ride share, please map from 3050 K Street and then walk towards the fountain on the waterfront until you see the restaurant.
If you plan to drive, Colonial Parking Garage (“Washington Harbour Parking”) is located on K Street between 30th and Thomas Jefferson Streets. The cost is currently $13 per car after 5 PM, and there is a vehicle height limit of 6’2”. Veer right and take the ramp down to the P2 level. Upon entering the P2 level, stay straight at the bottom of the ramp and use the elevator diagonally across from the attendant’s booth in the P-2 orange area. (You can also look for signs pointing you towards Sequoia’s elevator.) Take the elevator to Level 1 which brings you directly into the main dining room or Level 2 which will take you to the mezzanine level. If you park on the P1 level, you will exit the garage on the opposite side of Washington Harbour.
Once you enter the restaurant on the main floor, you will be greeted with signage and directional personnel to show you to the State Room.