The Summer Institute in Computational Social Science (SICSS)(https://sicss.io/2026/melbourne/) returns to Australia next week, bringing together 19 early-career researchers from ten universities across Australia and beyond for two intensive weeks of computational social science.
Running from 22 June to 3 July 2026, SICSS-Melbourne is hosted across RMIT University and Deakin University’s Faculty of Arts and Education, and delivered by the Australian Internet Observatory and the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S), with support from the Australian Research Data Commons. The program is organised by Bogdan Mamaev and Kateryna Kasianenko.
The first week moves from the big questions of the field through to hands-on practice. It opens with a keynote dialogue: What is Computational Social Science, and Why It Matters in Australia? featuring Daniel Angus, Olga Boichak, and Svetha Venkatesh, and continues with Ahrabhi Kathirgamalingam on social bias in CSS and a panel on research ethics with Dominique Carlon, Ehsan Dehghan, and Olga Boichak.
Much of the week is devoted to the data collection methods and tools at the heart of the AIO’s work. Sessions cover data donation and data download packages (DDPs) with Kellie Vella, Lauren Hayden, Michael Esteban, and Dan Tran; mobile screen capture; and the aired dashboard for Australia-wide social media research, presented by Richard Sinnott.
Participants also work with text and large language models alongside Kim Doyle, Daniel Russo-Batterham, and Seraphine F. Maerz; explore Retrieval-Augmented Generation (RAG) with Futoon Abushaqra and Sachin Pathiyan Cherumanal; and take on large-scale image analysis with Kunal Chand. The week also closes with panels on cross-disciplinary collaboration, working in industry, careers and grant writing, featuring multiple guests, including Johanne Trippas, Laura Gartry, Ariel Kuperman, Indigo Holcombe-James, Andrew McMahon (ABS) and Stephen Wan (CSIRO).
Throughout, the program returns to a set of guiding questions: how to collect digital data ethically and responsibly, how to recognise and manage bias, how to validate computational findings, and what computational social science can actually deliver for research in the Australian context.
In the second week, participants form interdisciplinary teams and put the methods into practice, building real research projects supported by drop-in experts and mentors from the program’s industry partners. Teams present their findings on the final day — work that we hope will grow into genuine research outputs, new collaborations and lasting skills.
SICSS-Melbourne is, above all, an interdisciplinary effort. This year’s cohort and presenters span disciplines, methods and institutions — from the University of Sydney, Monash, RMIT, the University of Melbourne, QUT, Deakin, the University of Queensland, James Cook University and the Australian National University, among others. By bringing scholars from different fields together, the institute aims to build a broader and stronger community of computational social science researchers in Australia.
The full program is available at sicss.io/2026/melbourne.
