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University of Cape Town
Summer Institute in Computational Social Science Partner Site

June 17, 2019 - June 28, 2019 | University of Cape Town

Partner location for SICSS organised at Princeton University

A Summer Institute in Computational Social Science will be held at the University of Cape Town from 17-28 June 2019. The purpose of the Summer Institute in Cape Town is to bring together graduate students, postdoctoral researchers, and faculty interested in computational social science. The Summer Institute is for both social scientists (broadly conceived) and data scientists (broadly conceived).

The organizer and principal faculty of the Summer Institute in Cape Town is Dr Visseho Adjiwanou. It is supported by the University of Cape Town, Russell Sage Foundation, Alfred P. Sloan Foundation, and the International Union for the Scientific Study of Population (IUSSP).

The instructional program will involve lectures (mostly livestreamed from Princeton University), group problem sets, and participant-led research projects. There will also be outside speakers who conduct computational social science research in academia, industry, and government. Topics covered include text as data, website scraping, digital field experiments, non-probability sampling, mass collaboration, and ethics. There will be ample opportunities for students to discuss their ideas and research with the organizers, other participants, and visiting speakers. Since we are committed to open and reproducible research, all materials created by faculty and students for the Summer Institute will be released open source.

Participation is restricted to Ph.D. students, postdoctoral researchers, and faculty from South Africa and sub-Saharan Africa. However, there are no restrictions based on citizenship, country of study, or country of employment. All cost of participations (Ticket, accommodation, meals, registration) fees are all covered.

About twenty five to thirty participants will be accepted. Participants with less experience with social science research will be expected to complete additional readings in advance of the Institute, and participants with less experience coding will be expected to complete a set of online learning modules on the R programming language. Students doing this preparatory work will be supported by a teaching assistant who will hold online office hours before the Institute.

Application materials should be received by Monday, March 25, 2019.

Applications that are not complete by the deadline may not receive full consideration. We will notify applicants solely through e-mail in mid-March, and will ask participants to confirm their participation very soon thereafter. Inquiries can be sent to cssforafrica@gmail.com

International Union for the Scientific Study of Population logo


Vissého Adjiwanou

Vissého Adjiwanou is Adjunct Senior Lecturer in Demography and Quantitative Methods at the University of Cape Town (South Africa), Associate Professor in Sociologie (Université du Québec à Montréal (UQAM, Canada). His research interests include maternal and reproductive health, family dynamics, and female employment in sub-Saharan Africa. Vissého is the chair of the Panel on Computational Social Science at the Union for African Population Studies (UAPS).

Image of Tom Moultrie

Tom Moultrie

Tom Moultrie is Professor of demography, and Director of the Centre for Actuarial Research (CARe) at the University of Cape Town. His interests lie in the technical measurement and sociology of fertility in sub-Saharan Africa, and the sociology of demographic measurement. He holds a BBusSc (Actuarial Science) from UCT, a MSc (Development Studies) from the LSE, and a PhD from LSHTM.


Matthew Salganik

Matthew Salganik is Professor of Sociology at Princeton University, and he is affiliated with several of Princeton’s interdisciplinary research centers: the Office for Population Research, the Center for Information Technology Policy, the Center for Health and Wellbeing, and the Center for Statistics and Machine Learning. His research interests include social networks and computational social science. He is the author of the book Bit by Bit: Social Research in the Digital Age.

Chris Bail

Chris Bail is the Douglas and Ellen Lowey Associate Professor of Sociology and Public Policy at Duke University and a member of the Interdisciplinary Program on Data Science, the Duke Network Analysis Center, and the Duke Population Research Institute. His research examines how non-profit organiations and other political actors shape social media discourse using large text-based datasets and apps for social science research. He is the author of Terrified: How Anti-Muslim Fringe Organizations Became Mainstream.

Megan Bruwer

Megan Bruwer is a transportation engineer with a background in civil engineering. She joined the Civil Engineering Department of Stellenbosch University in 2015 as a lecturer and project coordinator of the Stellenbosch Smart Mobility Laboratory (SSML) researching ITS solutions for developing countries. Prior to joining Stellenbosch University, Megan worked as a transport engineering consultant, involved in the implementation and operational design of public transport systems and road based traffic accommodation for new developments. Her research interests include traffic flow theory and the application of Intelligent Transport Systems to improve traffic data collection for transport planning and traffic management. She is currently completing a PhD in this field.

Marshini Chetty

Marshini Chetty will be joining the Department of Computer Science at the University of Chicago in August 2019. She specializes in human-computer interaction, usable security, and ubiquitous computing. Marshini designs, implements, and evaluates technologies to help users manage different aspects of Internet use from privacy and security to performance, and costs. She often works in resource-constrained settings and uses her work to help inform Internet policy. She has a Ph.D. in Human-Centered Computing from Georgia Institute of Technology, USA and a Masters and Bachelors in Computer Science from University of Cape Town, South Africa. Marshini is currently a research scholar in the Department of Computer Science at Princeton University and prior to that, she was an assistant professor in the College of Information Studies at the University of Maryland, College Park. Her work has won best paper awards at CHI and CSCW and has been funded by the National Science Foundation, the National Security Agency, Intel, Microsoft, Facebook, and multiple Google Faculty Research Awards.

Nick Feamster

As of July 2019, Nick Feamster is Neubauer Professor of Computer Science and the Director of Center for Data and Computation (CDAC) at the University of Chicago. Previously, he was a full professor in the Computer Science Department at Princeton University, where he directed the Center for Information Technology Policy (CITP); prior to Princeton, he was a full professor in the School of Computer Science at Georgia Tech. His research focuses on many aspects of computer networking and networked systems, with a focus on network operations, network security, and censorship-resistant communication systems. He received his Ph.D. in Computer science from MIT in 2005, and his S.B. and M.Eng. degrees in Electrical Engineering and Computer Science from MIT in 2000 and 2001, respectively. He was an early-stage employee at Looksmart (acquired by AltaVista), where he wrote the company’s first web crawler; and at Damballa, where he helped design the company’s first botnet-detection algorithm.

Image of Kyle Finlay

Kyle Finlay

Kyle runs an international data science team for a large market research firm. His team focuses on R&D, including in areas such as networks and NLP. In his spare time, he maintains a blog that applies a computational social science lens to understanding South African politics on social media.

Vukosi Marivate

Vukosi Marivate holds a PhD in Computer Science (Rutgers University, as a Fulbright Scholar). He is a senior Data Scientist and acting research group leader for Data Science at the CSIR, focusing on creating/using Machine Learning/Artificial Intelligence to extract insights from data to tackle societal challenges. Vukosi is an organiser of the Deep Learning Indaba, the largest Machine Learning/Artificial Intelligence workshop on the African continent, aiming to strengthen African Machine Learning. He supervises postgraduate students and leads the CSIR’s Data Science student development program.

Image of Hussein Suleman

Hussein Suleman

Hussein Suleman is Head of Department and Associate Professor in Computer Science at the University of Cape Town. Hussein’s main research interests are in digital libraries, ICT4D, African language information retrieval, cultural heritage preservation, Internet technology and educational technology. He has in the past worked extensively on architecture and interoperability issues related to digital library systems, with a growing emphasis on the relationship between low resource conditions and such architectures.

Teaching Assistants

Aldu Cornelissen

Aldu Cornelissen is a lecturer at the Department of Information Science at Stellenbosch University. He co-found the Computational Social Science group at Stellenbosch University, and is a member of the Centre of Artificial Intelligence (CAIR). The group’s research focuses on the impact of social media in society by investigating bot interference during political elections in Sub-Sahara Africa. Aldu specialises in Social Network Analysis, specifically individual and group social cognition.

Emmanuel Olamijuwon

Emmanuel Olamijuwon is a lecturer at the University of Eswatini, and a PhD candidate in demography and population studies at the University of the Witwatersrand, South Africa. His research uses social media, digital tools and also adapts computational approaches in helping adolescents and young African adults make better and informed decisions about their sexual and reproductive health. Emmanuel also plays an active role in various interdisciplinary research projects many of which revolve around the social determinants of health, as well as sexual and reproductive health. He is the coordinator of SHYad.NET


Image of Nyamador Komla David Adenyo

Nyamador Komla David Adenyo

Nyamador Komla David Adenyo is a PhD candidate in Statistics and Probability, at the Institute of Mathematics and Physical Science , University of Abomey-Calavi (Benin). He got a Master degree in Statistics and Probability. His research interests is Dynamic Panel data models with interactive fixed effects.

Image of Lateef Amusa

Lateef Amusa

Lateef Amusa is a lecturer at the University of Ilorin, Nigeria. He is currently rounding up his PhD programme in Applied Statistics at the University of Kwazulu-Natal, South Africa. He holds a BSc (First class honours) and a master’s degree in Statistics from the University of Ilorin, Nigeria. His research interests include the use of Spatial and data mining models, big data analytic methods with application to social science, health and medicine.

Image of Boladé Hamed Banougnin

Boladé Hamed Banougnin

Boladé is a demographer with work experience of about six years in design and data collection, data processing, analysis, interpretation, and dissemination. In 2012, he graduated from the Institut de Formation et de Recherche Démographiques—a regional institute for population studies—of the University of Yaoundé (Cameroon). He is currently undertaking his Ph.D. study in Reproductive Health Science at the Panafrican University, Life and Earth Sciences Institute at the University of Ibadan, Nigeria. His past and ongoing projects examine the relationship between poverty and fertility, the fertility of migrants in urban areas, the stall in fertility decline in Sub-Saharan Africa. He has also been teaching a variety of courses in demography and statistics at the University of Parakou and Abomey-Calavi (Benin) since 2014. Prior to this position, he worked as an intern at the Benin national institute of statistics where he was involved in several population and development projects.

Image of Garikayi Chemhaka

Garikayi Chemhaka

Garikayi Chemhaka is a lecturer at the University of Eswatini. His current research interests focuses on sexual and reproductive health, family formation and fertility. His broad interests are in traditional quantitative methods and use of online data. Garikayi holds a PhD from University of the Witwatersrand, an MPhil from UCT, and MSc from University of Zimbabwe (UZ) in Demography and Population Studies. He received his Bachelor’s degree in Statistics from UZ.

Image of Fidelia Dake

Fidelia Dake

Dr. Fidelia Dake is a Lecturer at the Regional Institute for Population Studies at the University of Ghana. She holds a Doctor of Philosophy and a Master of Philosophy in Population Studies. She also holds a Master of Science in Global Ageing and Policy and a Bachelor of Science in Nutrition and Food Science. Her research focuses broadly on health demography, public health, and international health and development. Her interests include nutrition and physical activity, obesity and non-communicable diseases, socio-environmental determinants of health, urban health, health statistics (including vital statistics), and health-financing, particularly, universal health coverage. Her current research examines transportation-related physical activity and the public health impacts of physical inactivity.

Image of Justin Dansou

Justin Dansou

Justin got a PhD degree in Reproductive Health from the Pan African University Institute for Life and Earth Sciences (PAULESI), located at the University of Ibadan, Ibadan, Nigeria. Prior to his doctoral studies, he graduated with a master’s degree in Demography at the Institut de Formation et de Recherche Démographiques (IFORD) in Cameroon, and a Bachelor of Science degree in computing management at the Institut Universitaire de Technologie (IUT) of Université de Parakou in Benin. He worked as research assistant at the Institut de Formation et de Recherche Démographiques (IFORD). Currently, he gives lectures pertaining to demographic analysis at the École Nationale de la Statistique, de la Planification et de la Démographie (ENSPD) at the Université de Parakou. His research interest includes Population and Health; Reproductive Health including Maternal health and Child survival.

Image of Dereje Danbe Debeko

Dereje Danbe Debeko

Dereje Danbe Debeko is an assistant professor at Department of Statistics, Hawassa University. He had intensive research and teaching experience in last 11 years from where he was hired as graduate assistant at Aksum University in 2009. He has thought different practical and theoretical statistics courses for the last eleven years. Dereje have been involved and had good research experience in area of longitudinal data analysis. His research interest mainly focuses on modeling hierarchical and repeated observations trends in various fields of studies. Currently, Dereje is in the position of “Associate dean for research and technology transfer” at College of natural and computational sciences, Hawassa University.

Image of Chodziwadziwa Whiteson Kabudula

Chodziwadziwa Whiteson Kabudula

Chodziwadziwa Whiteson Kabudula is a Senior Researcher and Head of Data and Analysis at the MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand, South Africa. His research interest is on the application of demographic, statistical, computational and informatics techniques to investigate population-level morbidity, mortality and utilization of health services, and their social determinants in rural settings in Sub Saharan Africa.

Image of Reesha Kara

Reesha Kara

Reesha Kara holds a Master’s Degree in Population Studies from the University of KwaZulu-Natal and is in the final year of her PhD at Rhodes University. Her research focuses on marriage and childbearing among middle-aged women in South Africa. Using social statistics, Reesha’s work identifies changes in trends of non-marital fertility among middle-aged women, key determinants of these trends and what these changes could possibly mean when focusing on the family as the basic building block of society. Reesha’s research interests include family formation structures, gender dynamics within relationships, social statistical methodologies, adolescent fertility and safe sexual and reproductive behaviours. Reesha has completed a number of training courses in social statistical methods and aims to use her research to highlight the value and importance of using social statistics to understand complex social behaviour and phenomenon.

Image of Caroline Kiarie

Caroline Kiarie

Caroline Kiarie is a PhD candidate at University of Kwazulu Natal in Durban, South Africa and a tutor fellow in the same institution. She holds a Masters in Science degree in Communication and Marketing from Franklin University in Ohio, USA. Her research interests include interpersonal communication, social media and social networks among employees. While in Kenya, she lectures corporate communication and public relations courses at Daystar University and Jomo Kenyatta University of Agriculture and Technology (JKUAT). She specializes in corporate communication and public relations and has worked and trained with several organizations both in Kenya and USA.

Image of Dagnon Eric Koba

Dagnon Eric Koba

Dagnon Eric Koba is a doctoral student at the Institut de Formation et de Recherche Démographiques (IFORD) at the University of Yaoundé II in Cameroon. With expertise in Demography, Digital demography and Social Statistics, his main research interests include, women’s reproductive health, gender inequality and migration.

Image of Wim Louw

Wim Louw

Wim Louw is a Senior Research Associate at J-PAL Africa. He works on randomized evaluations of signaling mechanisms in active labour markets, focusing on youth employment in Gauteng, South Africa. Before joining J-PAL, Wim worked as a researcher in the South African non-profit sector. Wim holds a master’s degree from the London School of Economics and Political Science in social research methods, and from the University of KwaZulu-Natal in linguistics. Interests include: causal inference, metrics, political economy and governance, text analysis, applied machine learning for economics, reproducibility and open source development.

Image of Katleho Makatjane

Katleho Makatjane

Katleho Makatjane is a PhD candidate in applied business statistics at the North West University Mafikeng campus South Africa and senior member of the South African Statistical Association (SAS) and certificated member of the Institute of Certificated and Chartered Statisticians of South Africa (ICCSSA). His research interests are focused on Financial forecasting, business analytic and risk analysis.

Image of Kathryn McDermott

Kathryn McDermott

Kathryn is a Junior Research Fellow based at J-PAL Africa at the University of Cape Town. She has a Masters in Economics from Stellenbosch University. She does research about water and electricity use and household purchasing patterns. Her interests are in using non-traditional data for research and helping policy makers use administrative data to inform their policy decisions.

Image of Elton Mukonda

Elton Mukonda

Elton is currently a PhD student and Research Fellow in the Division of Epidemiology & Bio-statistics, University of Cape Town. He is a trained demographer and statistician with extensive experience in data management, statistical analysis and modelling. His research focuses on the use of simulation modelling to solve public health problems while his current work focuses on maternal and child health issues in the context of HIV and other co-morbidities. Other fields of interest include Bayesian Statistics, Simulation and Optimization, Decision Analytic, Modelling for Economic Evaluation, Statistical Learning, Big Data Analytics and Chronic Disease Monitoring.

Image of Ronald Musizvingoza

Ronald Musizvingoza

Ronald Musizvingoza is a Social Scientist with a background in Sociology, Demography and Statistics. He is currently pursuing a PhD in Sociology at Bursa Uludağ University in Turkey. He is working on the Social Determinants of Maternal Health in Zimbabwe. Furthermore, he received training in data analysis and demographic analysis. His research interests are sustainable development goals (gender, health and inequality), migration and ageing. He is also currently interested in exploring the use of big data to achieve SDGs, especially in developing countries.

Image of Larissa Nawo

Larissa Nawo

Larissa Nawo has just finished her Ph.D. in Applied Economy policy and Analysis at the University of Dschang, Cameroon. Currently, Larissa is a research fellow cohort 2019 at the Structural Transformation of African Agriculture and Rural Spaces (STAARS) project of Cornell University. Her research interest is an intersection between development economics and data analysis studies, which include but not restricted to natural resources revenues management, behaviour sciences, impact evaluation techniques, computable general equilibrium (CGE) modelling, computational social science methods, applied micro econometric and applied political economy. During her doctoral studies, she was a Ph.D. visiting fellow at the United Nations University World Institute for Development Economics Research (UNU-WIDER) in Helsinki (Finland).

Image of Sindiso Ndlovu

Sindiso Ndlovu

Sindiso Ndlovu is a doctoral candidate in Demography and Population studies at the University of Witwatersrand in South Africa. She hold a Masters and Honours degree in Health Demography and her research interests lie in the field of family and health demography with specific focus on fertility, child health and policy. Her PhD thesis focuses on the intersection of health and family demography in a SSA countries.

Image of Baruwa Ololade

Baruwa Ololade

Baruwa Ololade is a doctoral student of Population and Health Studies at North West University Mafikeng, South Africa. Prior to this, he had completed his master’s Degree at the University of Witwatersrand, Johannesburg South Africa. Beside his educational profile, he is also an associate researcher with the International Organisation for Migration/Wits School of Public Health. Baruwa have worked at various organizations and played active roles in dealing with interdisciplinary research projects such as social determinant of health, sexual and reproduction health, maternal and child health and HIV/AIDS among migrants among many others.

Douglas Parry

Douglas is a PhD candidate and junior lecturer at the Department of Information Science at Stellenbosch University in South Africa. As a member of the Cognition and Technology Research Group (CTRG) his research concerns the interplay between digital technologies, human cognition, behaviour, performance, and affective well-being across a variety of situations and contexts. He holds a bachelor’s degree majoring in Socio-Informatics and Economics, Honours and Master’s degrees in Socio-Informatics and is currently working towards a doctoral degree specifically focusing on media multitasking and cognitive control. The common thread across his projects rests on an interest in understanding how people use technology, how this use is shaped by personal, situational and societal factors and, in addition, how behaviour with technology shapes our personal, social, and working lives. He has experience with traditional, experimental and data-driven research projects across a variety of academic domains.

Image of Arsene B. Sandie

Arsene B. Sandie

Arsene B. Sandie is completing his Ph.D in Mathematics-Statistics at Pan African University at Nairobi. He had mixed academic background, which intersects within mathematics and computer science (Bsc), applied statistics (Msc) and demography studies (Msc). His current research is about developing statistical methods for the design and analysis of clinical trials. Nowadays, he is aspiring to capitalize his multidisciplinary background, the computational social science area is then a great and exciting opportunity for that purpose.

Image of Patrick Tenga Shako

Patrick Tenga Shako

Patrick Tenga Shako is a Junior Lecturer/Teacher Assistant attached to the faculty of Computer sciences at the Nouveaux Horizons University and a candidate for a postgraduate degree at the University of Lubumbashi. Holder of an honour degree from the University of Lubumbashi and a master’s degree from the African Institute for Mathematical Sciences in Senegal, he has developed a real interest for data sciences, numerical analysis and mathematical modelling. After attending schools on big data, computational neuroscience, he acquired a real passion for artificial intelligence (Machine Learning, Reinforcement Learning). From this, he understood that one cannot do data analysis without understanding the domain in which these data belong. He expects to specialize in data science and mathematical modelling and plans to establish in the coming years an interdisciplinary research laboratory in data sciences in order to promote interaction and complementarity between different fields.

Image of Henry Wandera

Henry Wandera

Henry Wandera is pursuing MIT in data science at University of Pretoria. He holds BSc Honours in Computer Science at University of Pretoria and BSc in Science Education at Busitema University - ganda. He is passionate about promoting technology usage in developing countries and applying data science for social good. His interests contribute to how policies may influence users’ perspectives and towards understanding the impact of policies on the use of technologies in educational context. In his MIT, he is applying machine learning algorithms to predict school performance in African countries (Sierra Leone, South Africa) using non-traditional data.

Image of Chipo Zidana

Chipo Zidana

Chipo Zidana holds a PhD in Statistics from Cukurova university, Turkey, which was funded by the Turkish Government. She is currently a lecturer in the Department of Applied Mathematics at the National University of science and Technology, Zimbabwe. She has published work in population health and her current research focuses on machine learning approach to problems in rural livelihoods and health.


As we discussed in our call for applications, we have arranged two types of training prior to the event this summer. Some students have more sophisticated coding skills but little exposure to social science; other students have significant exposure to social science but lack strong coding skills.


The majority of the coding work presented at the 2019 SICSS will employ R. However, you are welcome to employ a language of your choice- such as Python, Julia, or other languages that are commonly used by computational social scientists. If you would like to work in R, we recommend that you complete the following courses within DataCamp, a website that teaches people how to code. Obviously, you only need to complete the classes with material that you would like to learn.

Additional readings will be provided on sub-Saharan Africa perspectives.

If you cannot afford datacamp, check out Chris Bail’s Intro to R slides at http://www.chrisbail.net/p/learn-comp-soc.html, or Charles Lanfear’s course at [https://clanfear.github.io/CSSS508/] or Grolemund and Wickham’s online book [https://r4ds.had.co.nz/].

Reading List

Our institute will bring together people from many fields, and therefore we think that asking you to do some reading before you arrive will help us use our time together more effectively. First, we ask you to read Matt’s book, Bit by Bit: Social Research in the Digital Age, which is a broad introduction to computational social science. Parts of this book will be review for most of you, but if we all read this book ahead of time, then we can use our time together for more advanced topics.

Also, for students with little or no exposure to sociology, economics, or political science, we have assembled a collection of exemplary papers in the core areas addressed by the Russell Sage Foundation. Neither your work nor the work we develop together at the institute need map neatly onto these categories, but if those with less exposure to social science read these, we will increase the chances of interdisciplinary cross-pollination, which we view as critical to the future of computational social science.

Future of Work

Behavioral Economics

Race, Ethnicity, and Immigration

Social Inequality

Schedule and materials

Sunday June 16, 2019

  • Opening Dinner

Monday June 17, 2019 - Introduction and Ethics

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-10:00 Welcome

  • 10:00-10:45 Logistics - Vissého Adjiwanou

  • 10:45-11:00 Coffee Break

  • 11:00-12:00 Introduction to Computational Social Science: an African perspective - Vissého Adjiwanou

  • 12:00-1:00 Lunch

  • 1:00-3:00 Guest speaker and discussion: Tom Moultrie

  • 3:00-3:30 Logistics (No livestream)

  • 3:30-4:00 Introduction to computational social science (livestream from Princeton)

  • 4:00-4:30 Why SICSS? (livestream from Princeton)

  • 4:30-4:45 Coffee Break

  • 4:45-5:30 Ethics: Principles-based approach (livestream from Princeton)

  • 5:30-6:15 Four areas of difficulty: informed consent, informational risk, privacy, and making decisions in the face of uncertainty (livestream from Princeton)

  • 6:15-8:00 Dinner & discussion

  • 8:00-10:00 Flash talk and tutorial : R Tidyverse (Optional)

Tuesday June 18, 2019 - Collecting Digital Trace Data

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-10:45 Group Exercise on Ethics

  • 10:45-11:00 Coffee Break

  • 11:00-12:00 Group Exercise

  • 12:00-1:00 Lunch

  • 1:00-3:00 Guest speaker and discussion : Kyle Finlay

  • 3:00-3:15 Coffee Break

  • 3:15-3:30 What is digital trace data? (livestream from Princeton)

  • 3:30-3:45 Strengths and weakness of digital trace data (livestream from Princeton)

  • 3:45-4:15 Screen-Scraping (livestream from Princeton)

  • 4:15-4:30 Coffee Break

  • 4:30-5:00 Application Programming Interfaces (livestream from Princeton)

  • 5:00-6:30 Building Apps and Bots for Social Science Research (livestream from Princeton)

  • 6:30-8:00 Dinner & discussion

  • 8:00-10:00 Flash talk and tutorial : R Markown (Optional)

Wednesday June 19, 2019 - Automated Text Analysis

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-10:45 Group Exercise on Digital Trace Data

  • 10:45-11:00 Coffee Break

  • 11:00-12:00 Group Exercise on Digital Trace Data

  • 12:00-1:00 Lunch

  • 1:00-3:00 Guest Speaker and discussion : Hussein Suleman

  • 3:00-3:15 Coffee Break

  • 3:15-3:30 History of quantitative text analysis (livestream from Princeton)

  • 3:30-3:45 Basic Text Analysis/GREP (livestream from Princeton)

  • 3:45-4:00 Dictionary-Based Text Analysis (livestream from Princeton)

  • 4:00-4:15 Coffee Break

  • 4:15-5:15 Topic models / Structural Topic Models (livestream from Princeton)

  • 5:20-6:30 Text Networks (livestream from Princeton)

  • 6:30-8:00 Dinner & discussion

  • 8:00-10:00 Flash talk and tutorial : Graphics in R with ggplot2 (Optional)

Thursday June 20, 2019 - Surveys in the Digital Age

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-10:45 Group Exercise on Text Analysis

  • 10:45-11:00 Coffee Break

  • 11:00-12:00 Group Exercise on Text Analysis

  • 12:00-1:00 Lunch

  • 1:00-3:00 Guest Speaker and discussion : Marshiny Chetty

  • 3:00-3:15 Coffee Break

  • 3:15-3:45 Survey research in the digital age (livestream from Princeton)

  • 3:45-4:15 Probability and non-probability sampling (livestream from Princeton)

  • 4:15-4:30 Coffee break

  • 4:30-5:00 Computer-administered interviews ans wiki surveys (livestream from Princeton)

  • 5:00-6:30 Combining surveys and big data (livestream from Princeton)

  • 6:30-8:00 Dinner & discussion

  • 8:00-10:00 Flash talk and tutorial : Introduction to Python (Optional)

Friday June 21, 2019 - Machine learning

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-10:45 Group Exercise on Surveys

  • 10:45-11:00 Coffee Break

  • 11:00-12:00 Group Exercise on Surveys

  • 12:00-1:00 Lunch

  • 1:00-3:00 Machine learning (Nick Feamster)

  • 3:00-3:15 Coffee Break

  • 3:15-4:45 Machine learning (Nick Feamster)

  • 4:45-5:00 Coffee break

  • 5:00-6:30 Machine learning (Nick Feamster)

  • 6:30-8:00 Dinner & discussion

  • 8:00-10:00 Flash talk and tutorial :

Saturday June 22, 2019 - Experiments

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-10:45 Group Exercise on Machine learning

  • 10:45-11:00 Coffee Break

  • 11:00-12:00 Group Exercise on Machine learning

  • 12:00-1:00 Lunch

  • 1:00-3:00 Guest Speaker and discussion - Aldu Cornelissen

  • 3:00-3:15 Coffee Break

  • 3:15 - 3:45 What, why, and which experiments? (livestream from Princeton)

  • 3:45 - 4:15 Moving beyond simple experiments (livestream from Princeton)

  • 4:15 - 4:30 Coffee break

  • 4:30 - 5:15 Four strategies for experiments (livestream from Princeton)

  • 5:15 - 5:45 Zero variable cost data and musiclab (livestream from Princeton)

  • 5:45 - 6:15 3 Rs (livestream from Princeton)

  • 6:30-8:00 Dinner & discussion

Sunday June 23, 2019 - Day off

Monday June 24, 2019 - Work on group projects - With the presence of Vukosi Marivate

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-10:30 Speed-dating and group formation

  • 10:30-12:00 Group project

  • 12:00-1:00 Lunch

  • 1:00-2:00 Flash talks : Vukosi Marivate

  • 2:00-2:15 Coffee Break

  • 2:15-6:30 Group project

  • 6:30-8:00 Dinner & discussion

  • 8:00 - Group project

Tuesday June 25, 2019 - Work on group projects

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-12:00 Group project

  • 12:00-1:00 Lunch

  • 1:00-2:00 Flash talks

  • 2:00-2:15 Coffee Break

  • 2:15-6:30 Group project

  • 6:30-8:00 Dinner & discussion

  • 8:00 - Group project

Wednesday June 26, 2019 - Work on group projects

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-12:00 Group project

  • 12:00-1:00 Lunch

  • 1:00-2:00 Flash talks

  • 2:00-2:15 Coffee Break

  • 2:15-6:30 Group project

  • 6:30-8:00 Dinner & discussion

  • 8:00 - Group project

Thursday June 27, 2019 - Work on group projects

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-12:00 Group project

  • 12:00-1:00 Lunch

  • 1:00-2:00 Flash talks

  • 2:00-2:15 Coffee Break

  • 2:15-6:30 Group project

  • 6:30-8:00 Dinner & discussion

  • 8:00 - Group project

Friday June 28, 2019 - Work on group projects

  • 9:00-9:15 Logistics (No livestream)

  • 9:15-12:00 Presentation of group projects

  • 12:00-1:00 Lunch

  • 1:00-2:00 Presentation of group projects

  • 2:00-2:15 Coffee Break

  • 2:15-5:00 Presentation of group projects and conclusion

  • 5:00-8:00 Closing dinner

Saturday June 29, 2019

  • Students depart

Live Stream

#For those unable to attend in person, we will be live-streaming each day from approximately 9:00am to 5:30pm ET. Group exercises and #some of the visiting speaker’s lectures will not be live-streamed. No registrations will be required to watch the livestream. We will #post addition information about the livestream here once it is avaiable.