From the evening of Sunday, July 28 to Friday, August 09, 2019, the University of Bamberg will host a partner event for the Summer Institute in Computational Social Science. The purpose of SICSS Bamberg is to bring together interested Master students, PhD students, postdoctoral students and faculty in Germany. The Summer Institute is for both social scientists (broadly conceived) and data scientists (broadly conceived).
The instructional program will involve lectures and group problem sets in the first week and participant-led research projects in the second week. Participants will be able to work in teams to learn how to implement the material from the lectures. Covered topics include ethics, web scraping and collecting digital trace data, automated text analysis, network analysis, digital field experiments, and surveys in the digital age. There will be ample opportunities for students to discuss their ideas and research with the organizers, other participants, and visiting speakers. One goal of this partner location is to build and expand the network of computational social scientists in Germany.
We are inviting applications from Master students, PhD students, postdoctoral researchers, and untenured faculty within 5 years of their PhD. Participants are expected to fully attend and participate in the entire two-week program. Participants with less experience with social science research will be expected to complete additional readings in advance of the Institute, and participants with less coding experience will be expected to complete a set of online learning modules on the R programming language. There is no cost for participating in the Summer Institute. For a limited number of participants, we will be able to cover housing and meal expenses up to a set cap.
Application materials were due Monday, February 25, 2019. We are no longer accepting applications.
We thank the Bamberg Graduate School of Social Sciences (BAGSS) for the generous support of this SICSS partner event.
We are also grateful for financial support from the Russell Sage Foundation and the Alfred P. Sloan Foundation.
All events will be held at:
University of Bamberg
Julian Hohner is a PhD candidate in Political Science at Bamberg University. He also works in the Management of the Bamberg Graduate School of Social Sciences and is particular interested in machine learning, quantitative text analysis, inferential statistics as well as populist, party and governmental behaviour studies. Moreover, Julian is participating as Teaching Assistant of the ECPR Winter/Summer Schools on a regular basis.
Thomas Saalfeld is Professor of Political Science at the University of Bamberg and Director of the Bamberg Graduate School of Social Sciences. Prior to joining Bamberg in 2009, he held research and teaching positions at the Universities of the German Federal Armed Forces Munich, Hull, Dresden, Kent and Bamberg. He was Member of the Council of the German Political Science Association from 2015 to 2016 and joined the Executive Committee of the European Consortium for Political Research (ECPR) in 2018. Since 2015 he has been the local organizer of the ECPR Winter School in Methods and Techniques. He has a particular interest in text-as-data applied to legislative studies.
Carsten Schwemmer is currently finishing a PhD in Sociology at Bamberg University, Germany. His research focuses on computational methods for the study of ethnic minorities and social media communication. Carsten is particularly interested in natural language processing, data mining and software development. He gave courses on computational social science at University of Bamberg, University of Constance and Humboldt University of Berlin.
Andreas Jungherr is a Juniorprofessor (Assistant Professor) for Social Science Data Collection and Analysis at the University of Konstanz. He studies the impact of digital media on politics and society. He has worked on the uses of digital media and technology by publics, political actors, and organizations in international comparison. He also addresses challenges for scientific research in reaction to digital change in order to realize opportunities emerging from new data sources and analytical approaches. In this, he has focused on harnessing the potential of digital methods and computational social science while addressing methodological challenges in its integration into the social sciences. Depending on the object under study, he also uses traditional quantitative and qualitative empirical approaches. Currently, he is lead investigator of ‘Communicative Power in Hybrid Media Systems’, a project financed by the Volkswagen Stiftung (2017-2020). The interdisciplinary project, featuring computer and information scientists, focuses on the interconnection between political coverage in legacy, online media, and political talk on online platforms in Germany, UK, USA, and South Korea.
Fariba Karimi is a researcher at the Department of Computational Social Science at GESIS – Leibniz Institute for the Social Sciences. She received her PhD in Physics with specialization in network science. Her current research focuses on computational approaches for addressing societal challenges such as gender inequality, bias in algorithms and sampling hard-to-reach groups and minorities. Her main expertise is analyzing large-scale socio-technical systems using network theory and data analysis.
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.
Oliver Posegga is an Assistant Professor at the Department of Information Systems and Social Networks at the University of Bamberg, an affiliate of the Center for Collective Intelligence at the MIT Sloan School of Management, and a principal investigator of the project ‘Communicative Power in Hybrid Media Systems’, funded by the Volkswagen Foundation. His research focuses on understanding the collective dynamics of digitally enabled networks, such as collective behavior and intelligence in organizational and societal settings, and touches a variety of topics, such as the dynamics of social networks, crisis management, crowdsourcing, data- and information quality, and discursive power in contemporary media systems.
Martijn Schoonvelde is an Assistant Professor in Political Science at University College Dublin. Prior to that, he was a Postdoctoral Fellow at the Vrije Universiteit Amsterdam and the University of Exeter and a Max Weber Fellow at the European University Institute in Florence. In his work, he analyzes the rhetoric of politicians. Is this rhetoric driven by strategy, ideology or aspects of their personality? Do they shift blame to others when topics are sensitive with the public? And when do they use emotional appeals? More broadly, his interests include political communication, EU politics, computational social science, and text as data.
Milena Tsvetkova is Assistant Professor at the Department of Methodology at the London School of Economics and Political Science. Prior to that, she was Postdoctoral Researcher in Computational Social Science at the Oxford Internet Institute at the University of Oxford. She holds a PhD in Sociology from Cornell University, where she worked with Michael Macy. Her interests reside in the field of computational social science. In her research, she uses large-scale web-based social interaction experiments, network analysis of online data, and agent-based modeling to investigate fundamental social phenomena such as cooperation, social contagion, segregation, and inequality.
Jonas Reissmann is a Master’s student in Survey Statistics at the University of Bamberg and holds a BA in Political Science from the same institution. He is particularly interested in R programming, quantitative modelling and the field of interest group research. Jonas has gained experience as a teaching assistant for statistics and R on various occasions both at the university and at the ECPR Winter School in Methods and Techniques.
I am a master student in the field of sociology at the University of Bamberg. My research focuses on applying computational methods for the studies of dynamic systems. I’m particularly interested in agent- based modeling, social network analysis and non-linear effects. I presented part of my research at the Historical network research conference last year and at the Studentischer Soziologiekongress 2017 in Chemnitz.
Meng Chen is an Assistant Professor in Communication at Webster University, Vienna. She is interested in utilizing computational analysis to explore the interactions among linguistic features of cancer patients’ online posts, their personal network structures, and social capital flow on social support platforms. Before coming to Vienna, she completed a PhD in Communication at University of California, Davis.
Johannes is a master’s student at the University of Essex and the University of Bamberg, where he is pursuing a degree in conflict resolution and political science. His main interest lies in cybersecurity and how governments respond to the emerging threat of high-level cyber attacks. In his master’s thesis, he is exploring potential macro-level determinants of interstate cyber disputes and their connection with the onset of more traditional types of warfare.
Andrea is a research assistant and a PhD candidate in International Relations at the University of Bamberg, Germany. Her primary research interest concerns the evolution of institutional complexes and their consequences on international governance. She has a keen interest in exploring how big data and computational social science can be used to advance the study of international politics in general and of inter-organizational networks in particular. She is also broadly interested in political sociology, social media, and computational analysis.
Julia is a PhD candidate at the London School of Economics and Political Science. Her research scrutinises how and when political actors strategically employ populism and which factors explain the variation in voting for populist parties in European countries since 1960. Julia is working on ways to measure and explain political stands using quantitative text analysis, causal inference and geo-spatial modelling. She holds an M.Sc. in Politics Research (University of Oxford) and a B.A. in Social Science (Humboldt University Berlin).
Marc Luettecke is a Master’s student in Social and Economic Data Science at the University of Konstanz. He holds a Bachelor’s degree in Finance from Loyola University New Orleans and a Master’s degree in Finance from the University of Texas (Austin). His preferred research interest lays with individual and group decision behavior, for which he currently learns techniques from the realm of Deep Learning and financial risk behavior for current class and research projects. His past endevaors include positions as a financial consultant and social involvement for housing projects in the Austin area.
Daniel Mayerhoffer is a PhD candidate at the chair for Political Theory, University of Bamberg and an M.A. student in Ethics of Textual Cultures at FAU Erlangen-Nuremberg. He received his B.A. in Philosophy & Economics from University of Bayreuth, an M.A. in Political Science from University of Bamberg and an M.Sc. in Social Research Methods from University of Surrey. Daniel develops agent based computational simulation models to understand and explain social, political and economic phenomena.
Qasim Pasta is Assistant Professor at Usman Institute of Technology. He recently received his Ph.D. (Network Science) from PAF-KIET, Pakistan. His recent work contributes to the development of network models enabling the embedding of ground-truth community structures. He is also leading an interdisciplinary research project SPLOP (Socio-Political Landscape of Pakistan) to analyze the usage of social media in the context of general and political conversation by people of different regions of Pakistan.
Liane Rothenberger is a senior researcher and lecturer at the Institute of Media and Communication Science at Technische Universität Ilmenau, Germany. Her research focuses on journalism and communication in an intercultural perspective, norms and values in communication studies and in the social sciences, and crisis communication.
Currently: MSc Computing in the Humanities. Before: BA Sociology & Psychology. Python, R, NLP, Knowledge Graphs, Understanding & Visualizing Data.
Aleksandra is a PhD candidate at the Institute of Communication and Media Studies, University of Bern, Switzerland. She focuses on political communication online and actively uses computational methods in her research. Aleksandra is particularly interested in news consumption on social media platforms, the role of social media in authoritarian regimes, algorithmic personalization, and polarization online. She also teaches social media analysis with R.
Franziska Weeber is currently pursuing her MSc in Social and Economic Data Science at the University of Konstanz. Her research interests include spatial aspects of inequality with a focus on gentrification and social segregation as well as spatial interaction in both small and large scale contexts. She is also interested in data retrieval using computational methods such as web scraping. Franziska holds a BA in sociology with a minor in computer science from the University of Konstanz. During her Bachelor, she completed an internship and a freelance contract for the Federal Statistical Office of Germany.
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 coding skills.
The majority of the coding work presented at the 2019 SICSS Bamberg 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 free RStudio Primers, which can be supplemented by the open access book R for Data Science by Garrett Grolemund and Hadley Wickham. RStudio Primers cover 6 topics: The Basics, Working with Data, Visualize Data, Tidy Your Data, Iterate, and Write Functions. If you already feel comfortable with these topics, then you do not need to complete these Primers.
If you would like more practice after completing the RStudio Primers, some other materials that we can recommend are:
The Summer Institute in Bamberg 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 Matthew Salganik’s book, Bit by Bit: Social Research in the Digital Age (Read online or purchase from Amazon, Barnes & Noble, IndieBound, or Princeton University Press), 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. 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.
The schedule will be posted in the coming weeks.