IMPORTANT NOTE: To attend this livestream lecture, prior registration is necessary: please send an email specifying your name and academic affiliation to firstname.lastname@example.org by 18 May
IMPORTANT NOTE: To attend this livestream lecture, prior registration is necessary: please send an email specifying your name and academic affiliation to email@example.com by 18 May 2020 (Monday) at the latest.
“Out with every theory of human behavior (…) who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.” In a now (in)famous article, Chris Anderson, the editor-in-chief of Wired magazine, made a claim that the data aggregated by technology companies is rendering scientific methods obsolete. Anderson argued that there is no need for sampling-based methodologies in an age wherein everything is recorded and everything leaves a digital trace. Whilst Anderson’s claims about the end of scientific method are at best ludicrous, he is right in pointing out that the “data deluge” has destabilized the epistemological claims of social science. To put it in another way, how can social science remain relevant in the age of data science? One way would be by harnessing the potential offered by computational social science, the fusion social science rigour with computer science techniques.
Computational social science focuses on developing methodologies to collect and analyse large quantities of data gleaned from social media and the Internet. Although such methods are interdisciplinary and diverse, they all tend to share three common features: automated or semi-automated collection of datasets from digital environments, large datasets and the usage of a range of different techniques drawn from computer science to model or analyse the results. Using examples from ongoing or published research, this lecture introduces three different categories of data (semantic, sentiment and relational) available online, and showcases some of methodological approaches to analyse and model such datasets. In doing so, the talk invites participants to critically engage with both the challenges and opportunities of computational methodologies.
Dr. Ivo Furman is assistant professor and graduate program director at Istanbul Bilgi University’s department of Media. He completed his PhD in Sociology at Goldsmiths College, University of London in 2015. His research has been supported by numerous institutions including the Arts and Humanities Research Council (AHRC), the Danish Agency for Science and Higher Education, Turkish Science and Technology Foundation (TUBITAK) and Stiftung Mercator. His research interests include computational social science methods, critical data studies and digital sociology. Featured on Policy & the Internet, his most recent publication, “End of an Habermassian Ideal? Political Communication on Twitter during the Night of the 2017 Turkish Constitutional Referendum”, uses network analysis to explore political polarization on social media. He is also co-editor of the upcoming volume Politics of Culture in New Turkey (Edinburgh University Press, 2021).