Excellent training in research methods is crucial for any field. Especially emerging fields like Computational Social Science which are not yet institutionalized in universities need opportunities to teach their methods to ensure excellent future research.
Each of three CSS summer schools will focus on a specific type of data (behavioral trace data, text data or multimedia data), their corresponding methods and selected relevant topics in social science.
The first summer school (2017) was on methods for analyzing and modeling behavioral trace data (e.g., sequential learning methods, models of user navigation and click streams, interaction network analysis, massive online experiments that allow to observe interactions) and students conducted projects in which they applied the newly learned methods to gain insights into social phenomena like prosocial behavior, consensus or mobility.
The second summer school (2018) focused on methods for textual data (e.g., sentiment analysis, latent semantic models, causal inference methods for text data). The topical focus of student's project work will be conflicts, radicalization, polarization and bias, since online discussions, blog posts and reactions to news articles may allow to understand why and how people radicalize over time.
The third summer school (2019) will go beyond text and focus on methods for analyzing multimedia data (e.g., computer vision methods, spatial and temporal analysis of urban spaces via multimedia content analysis, spreading and mutation models for multimedia content). In this school we will encourage and help students to explore cultural phenomena like social orientation and its expression for instance in urban spaces, images and art.
The event series is funded by Volkswagen Foundation.
Please find further information on the CSS Summer School Website: summerschool.computationalsocialscience.eu
The Symposium is an interdisciplinary venue that brings together researchers from a diverse range of disciplines to contribute to the definition and exploration of the societal challenges in Compuational Social Science, especially around the topics of inequality and imbalance to understand the role that digital technologies, the Web, and the algorithms used therein play in the mediation and creation of inequalities, discrimination and polarization. The series is funded by Volkswagen Foundation.
The third event of the symposium series will take place in Zurich, Switzerland. The overall subject will be polarization and radicalization. More information can be found on the symposium website.
GESIS promotes the formation and networking of an interdisciplinary Computational Social Science community by organizing international conferences, symposia, and workshops. Among those are the 3rd International Conference on Computational Social Science (IC2S2 2017) and the 10th International AAAI Conference on Web and Social Media (ICWSM-16), the European Symposium Series on Societal Challenges in Computational Social Science, the KickOff Workshop International Research in Computational Social Science and many more.
GESIS has established a Google Group open to all scientists who are interested in Computational Social Science as a digital forum for exchanging ideas, offering jobs, announcing events, and keeping in touch. Researchers from all disciplines are most welcome to join: http://tiny.cc/cssnet
The GESIS Computational Social Science (CSS) Seminar is a monthly event for expert exchange on data science and social analytics (conducted in English). It is held at GESIS, Cologne (Unter Sachsenhausen 6-8, 50667 Cologne) and open to all interested. Please find more information on past and upcoming talks here.