Summer Institute in Computational Social Science Partner Site

June 16 - June 29, 2019 | Oxford University

Partner location for SICSS organised at Princeton University

The Summer Institute in Computational Social Science (SICSS) brings together graduate students, postdoctoral researchers, and beginning faculty interested in computational social science. SICSS is for both social scientists and data scientists. SICSS started as an initiative at Princeton University in 2017. In 2019, we will be hosting a partner institute in Oxford for the first time. It will be held from the evening of Sunday, June 16 to the morning of Saturday, June 29, 2019 at Nuffield College. The aim of SICSS-Oxford is to build and expand a network of researchers interested in computational social science, bringing together individuals from across the University of Oxford and from other institutions.


SICSS-Oxford is being organized by former participants of the 2017 and 2018 SICSS workshops and will feature local speakers and live streams from Princeton. In the first week, participants at the Oxford location will also be able to work in teams to learn how to implement the material from the lectures and workshops. Participants will also be expected to present some of their work and research interests early on in the workshop. In the second week, participants will form teams to develop a research project related to computational social science.

The instructional program will involve lectures, group problem sets, and participant-led research projects. There will also be speakers who conduct computational social science research. Topics covered include text as data, website scraping and digital trace data, online experiments, non-probability sampling, machine learning, and ethics. There will be ample opportunities for students to discuss their ideas and research with the organizers, other participants, and visiting speakers. Because we are committed to open and reproducible research, all materials created by faculty and students for the Summer Institute will be released open source.


The Summer Institute in Computational Social Science is funded in part by grants from the Russell Sage Foundation and the Alfred P. Sloan Foundation. SICSS-Oxford is additionally supported by grants from Nuffield College and the TDEP Awards of the Oxford University Social Sciences Division. There are no registration fees for participating in SICSS-Oxford.

Participants are expected to attend both weeks of the institute. Meals and refreshments will be provided free of cost for all participants at SICSS-Oxford during the event. Accommodation for those participants from outside Oxford will also be covered. Travel costs (up to a set cap) will be reimbursed for those from outside Oxford.


We are inviting applications from Ph.D. students, postdoctoral researchers, and faculty within 7 years of their Ph.D. We are hoping to have wide participation from researchers across different departments and institutes within the University of Oxford, both from the social sciences and the computational/data sciences. We would also like to welcome a limited number of participants from other institutions both in the UK and abroad. 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.

The deadline for applications is Monday, April 15, 2019, 11.59 pm (UK). More information and instruction for applying can be found on our Apply page.


Ridhi Kashyap

Ridhi Kashyap is associate professor of social demography and fellow of Nuffield College at the University of Oxford. She completed her DPhil in Sociology jointly affiliated with the University of Oxford and Max Planck Institute for Demographic Research. Her research spans a number of substantive areas in demography and sociology, including gender, mortality and health, the diversification of family forms, and ethnicity and migration. Her work has sought to adopt computational innovations both in terms of modelling approaches such as agent-based models and digital trace data from web and social media platforms to study social and demographic processes. She is currently leading a Data2X and UN Foundation supported project that uses big data from the web, in particular large-scale online advertising data that provide information on the aggregate numbers of users of online platforms by demographic characteristics, to measure sustainable development and gender inequality indicators.

Image of Nicolo Cavalli

Nicolo Cavalli

Nicolò is a DPhil candidate in Sociology at Nuffield College, University of Oxford. He holds a BA in Politics from University of Bologna and a MSc in Economics from Bocconi University, Milan. Before joining Nuffield College, Nicolò worked as journalist, reporting on social issues and political movements from Italy, Greece, Catalunya, California and Peru. His Doctoral Thesis focuses on how intergroup emotional stratification emerged in Europe in times of economic recession.

Taylor Brown

Taylor Brown is a doctoral student in the Duke Sociology department, and is associated with the Duke Network Analysis Center. She has broad interests in computational methods and social media studies. Her dissertation explores gender inequality in creative professions. Taylor holds an MA in sociology from UNC-Chapel Hill and an MSc in evidence-based social intervention from the University of Oxford. Prior to beginning her PhD, Taylor fulfilled an appointment at the National Science Foundation in the division of Social and Economic Sciences.

Local Speakers

Pablo Barbera

Pablo Barberá is an Assistant Professor of Computational Social Science at the London School of Economics. His research develops text and network analysis methods that improve our understanding of how exposure to political information through social media sites affects political behavior. He is also the authors of several R packages that allow scholars to collect and analyze social media data.

Image of Mariarosaria Taddeo

Mariarosaria Taddeo

Dr Mariarosaria Taddeo is Research Fellow at the Oxford Internet Institute, University of Oxford, where she is the Deputy Director of the Digital Ethics Lab, and is Faculty Fellow at the Alan Turing Institute. Her recent work focuses mainly on the ethical analysis of Artificial Intelligence, cyber security , cyber conflicts, and ethics of digital innovation. Her area of expertise is Philosophy and Ethics of Information, although she has worked on issues concerning Epistemology, Logic, and Philosophy of AI. She has been listed among the top 50 most inspiring Italian women working in AI in 2018. Dr Taddeo has been awarded The Simon Award for Outstanding Research in Computing and Philosophy. She also received the World Technology Award for Ethics acknowledging the originality and her research on the ethics of cyber conflicts, and the social impact of the work that she developed in this area. Since 2016, Taddeo serves as editor-in-chief of Minds & Machines (SpringerNature) and of Philosophical Studies Series (SpringerNature).

Workshop Leaders

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Roberto Cerina

Roberto Cerina is a third-year DPhil candidate in Sociology at Nuffield College, University of Oxford, with an interest in Election Forecasting, Bayesian Statistics and non-representative surveys. His recent work has focused on making inference on electoral preferences from revealed behaviour on social-media; in particular, together with Professor Raymond Duch, he has forecasted the 2018 mid-term elections in Texas using likes from pages of public candidates on Facebook, leveraging the latest technology in prediction and post-stratification, and achieving results comparable to state-of-the-art surveys, at a fraction of the cost (see here from more: http://raymondduch.com/forecasts/). Currently he is working on forecasting the 2019 Indian Lok Sabha Elections using a convenience sample and Mechanical Turks. He is also working on finalising a Machine Learning pipeline to produce fully automated Opinion Polling from Twitter.

Image of Charles Rahal

Charles Rahal

Charles Rahal is a social science methodologist and applied social data scientist with a background in high-dimensional econometrics, having completed his PhD in 2016. He currently holds a British Academy Postdoctoral Fellowship entitled ‘The Social Data Science of Healthcare Supply’ which develops data driven tools for analysing healthcare procurement processes. He is particularly interested in unique data origination processes, be they unstructured or otherwise, and is an advocate for open source and reproducible academic research, particularly in the forms of Python, LaTeX and Linux. He was a co-recipient (with Aaron Reeves, Sam Friedman and Magne Flemmen) of the 2018 European Academy of Sociology Best Paper award, and he presently teaches ‘Python for Sociologists’ in Michaelmas Term. Other current areas of interest include civic technology, applied econometrics (predominantly spatial and time series), scientometrics, data wrangling, software development, and social stratification and social mobility. He is increasingly interested in sociological applications of text mining algorithms. Follow his projects on github and Google Scholar!

Teaching Assistants

To be announced.

Schedule and materials

Sunday June 16, 2019 - To be announced.

  • The schedule will be posted in the coming months.