The Image Machine

TheSummer Institutes in Computational Social Science(SICSS) is an international program created to train the next generation of social science researchers and incubate cutting-edge research across disciplinary boundaries. Since its inception at Princeton in 2017, the program has delivered training to more than 700 early-career researchers from 124 academic fields worldwide. In 2022, the University of Sydney became the first Australian university to host the Summer Institute at theSydney Social Sciences and Humanities Advanced Research Centre(SSSHARC). The Sydney Social Sciences and Humanities Advanced Research Centre is a collaborative research space designed to advance innovative research partnerships and methodologies across the humanities and social sciences.

Sydney CSS Lab

Explore a novel computational method for supporting the analysis of large image collections with an emphasis on visual social platforms.

SICSS-Festival

SICSS-Festival: a series of research workshops and events organised by SICSS-Sydney and hosted at the Sydney Social Sciences and Humanities Advanced Research Centre (SSSHARC).
Learn more about SICSS-Sydney: https://sicss.io/2022/sydney/ and @SICSSSydney

This workshop will introduce participants to a novel computational method for supporting the analysis of large image collections (Burgess et al., 2021), with a specific focus on images obtained from visual social platforms such as Instagram and Facebook. This novel method is an outcome of the ARC Discovery Project “Using machine vision to explore Instagram’s everyday promotional cultures” (Angus D., Burgess, J. &amp; Carah, N.). The workshop will provide an introduction to the machine learning methods involved in processing these images for a non-technical audience, and a hands-on session where participants will be able to trial the methods on their own computer using a pre-loaded dataset. Participants are not required to have any previous experience with advanced computational methods. This workshop will be of interest to scholars examining image data of various kinds, and at different scales (from close reading through to large 1000+ collections), and also to those scholars interested in critical algorithm studies.Burgess, J., et al. (2021). Critical simulation as hybrid digital method for exploring the data operations and vernacular cultures of visual social media platforms. doi: 10.31235/osf.io/2cwsu.For queries contact sicss.admin@sydney.edu.auDaniel AngusDaniel Angus is a Professor of Digital Communication, leader of the QUT Digital Media Research Centre’s Computational Communication and Culture Program, and Chair of Infrastructure within the ARC Centre of Excellence for Automated Decision Making and Society. His research examines issues at the intersection of technology and society, with a focus on algorithms, misinformation, and new methods to study the digital society.

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The Image Machine

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The Image Machine

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