We are seeking the opportunity to recruit an initial cohort of up to five PhD students to work on an interdisciplinary computational social science project under the supervision of the CSS Lab’s core faculty. The core faculty/supervision team includes:

• Dr. Olga Wojczak (Faculty of Arts, Communication and English, Faculty of Arts and Social Sciences)
• Professor Monika Bednarek (Faculty of Humanities and Social Sciences)
• Professor Eduardo G. Altmann (Department of Mathematical Statistics, Faculty of Science)
• Professor Kalervo Gulson (Faculty of Liberal Arts/Faculty of Social Welfare)
• Associate Professor Tristram Alexander (Department of Physics, Faculty of Science)
• Dr Aim Sinpeng (College of Liberal Arts/College of Socio-Political Science)
• Dr. Joanne Gray (Faculty of Arts, Communication and English, Faculty of Arts and Social Sciences)

All projects draw on the existing strengths and expertise of the Social Media and Data Science Research Group, as well as on the modeling and analysis of data-driven representations of individuals and communities, and the algorithmic biases associated with these emerging knowledge-producing regimes. Leverage the expertise of relevant faculty. The core faculty has strong research interests in three distinct areas of computational social science: language and topic modeling (Bednarek, Boichak), network analysis and community detection (Altmann, Alexander), and machine learning and artificial intelligence (Sinpeng, Grey). deliver outstanding results. , Garson). Coming from a variety of disciplines across two faculties, they have provided extensive graduate research leadership in relation to opportunities and introduced successful innovations to the HDR research training space.

We are looking for applicants with a background in computational social sciences, digital humanities, and/or data sciences, with regional and/or domain expertise. Successful candidates join a multidisciplinary research team in a lab located within the multidisciplinary and research-intensive environment of the Sydney Advanced Research Center for Social Sciences and Humanities (SSSHARC) at the University of Sydney. The supervisory team is typically made up of supervisors and co-supervisors with different backgrounds. This will expose PhD holders to different traditions of computational social sciences, allow them to tackle challenging research questions, and contribute to the creation of long-term interdisciplinary collaborations within the university.

Successful projects employ different approaches to critically understand big data and computation in sociotechnical contexts. In particular, various computational approaches (data visualization, corpus linguistics, topic modeling, network analysis, statistical machine learning, etc.) are seeking projects involving the creation, application, testing, or evaluation of news media, policy documents, etc.) to answer important theoretical and empirical questions to address socially important issues in contemporary society.

The theoretical social science framework underpinning the project can come from a variety of social science and humanities disciplines. Of particular interest are projects that investigate the development of algorithmic systems and policies and critically examine their social, cultural, and ethical implications. Projects may cover a wide range of social areas, including but not limited to human rights, public discourse, digital literacy, safety and security, educational outcomes, social studies of science, and more. Traditional method by triangulation of approach.