Until January 2022, Justin Ho was a postdoctoral research fellow at the Centre for European Studies and Comparative Politics working on the project: "What Do 'the People' Want? Analysing Online Populist Challenges to Europe", in which he investigates how populism is promoted through digital media using computational text analysis. He is also interested in nationalism, with a particular focus on its construction on social media. Justin is finishing a PhD in Sociology from the University of Edinburgh and holds an MSc in Political Theory from London School of Economics and Political Science.
- Social Media
- Computational Social Science
Ho, J.C. (2020) How biased is the sample? Reverse engineering the ranking algorithm of Facebook’s Graph application programming interface. Big Data & Society 7(1).
Ho, J.C. (2019) Assessing the Bias of Facebook's Graph API. ACM Hypertext and Social Media 2019.
Soldner, F., Ho, J.C., Makhortykh, M., Van der Vegt, I.W.J., Mozes, M. & Kleinberg, B. (2019) Uphill from here: Sentiment patterns in videos from left- and right-wing YouTube news channels. NLP+CSS at NAACL 2019.
Davidson, E., Ho, J.C. & Jamieson, L. (2019) Computational text analysis using R in Big Qual data: lessons from a feasibility study looking at care and intimacy. In: Weller, S. and Edwards, R. and Jamieson, L. & Davidson, E. (eds). Analysing large volumes of complex qualitative data - Reflections from a group of international experts. NCRM Working Paper.
All publications are available here
To know more
- Personal Website
- Github Repositories
- Twitter: @justin_ct_ho