The inner (net-)workings of authoritarian regimes...
My first research focus is situated in the growing subfield of studies on authoritarian regimes. I try to redirect the field's attention from irregular leadership change and formal institutions - like parties, elections, and parliaments - to the role of informal institutions in facilitating stable turnover among the leader's entourage. I propose that social network analysis offers a principled, but nevertheless nuanced, method to conceptualize and measure some informal institutions.
I elaborated on that idea in my dissertation, part of which was published in the Journal of East Asian Studies, and have further explored the more complex effect of having friends in high places in a study on networks formed in the Chinese Communist Party School published in Political Studies. In ongoing research projects (see below), I use expert survey data instead of publicly available CVs as a source for the influence and networks of Chinese political elites.
... and how do we learn about them
My published research is based mainly on publicly available information, which has become harder to obtain and less reliable in China and other authoritarian regimes such as Russia in the last few years. In the past, assessments of expert working in journalism, think tanks and academia - often called "China Watchers" or "Kremlinologists" in the case of the Soviet Union - had often filled such gaps. My current research projects thus deal with two alternative sources of information on elite politics: the first examines how one could automate the extraction of network information from unstructured text, such as newspaper articles and reports based on expert research and knowledge. In it, I use natural language processing and machine learning on a manually labeled training dataset of almost 5000 sentences from American elite politics, mostly from the Senate Intelligence Committee Report on Russian active measures during the 2016 US Elections and from newspaper articles on elite politics in the Trump White House. The other related research project, implemented together with Jos Elkink (University College Dublin) and Hans Hanpu Tung (National Taiwan University), surveys China experts to ask for the network connections among and the level of influence of Chinese political elites.
In both cases, I am particularly interested in how the network among the different sources of information may lead to an echo-chamber effect on the aggregate level: Do the social interactions among China experts influence their assessment of Chinese politics and elites? Do different newspapers report on similar parts or portray a similar image of political elite networks because they have access to the same sources or similar political leanings?
Information coordination networks on social media
My second research focus combines SNA and Political Communication to examine hidden disinformation campaigns (so-called political AstroTurfing) on social media. I argue that we can discover such campaigns by searching for networks of message coordination (i.e. accounts that tweet or retweet the same or similar content within a short time window), which are an almost inherent feature of such campaigns, because principal-agent problems make it difficult or very expensive to hide these tell-tale patterns. Together with an interdisciplinary and researchers in Germany (David Schoch and Sebastian Stier) and the US (JungHwan Yang), I documented those patterns in the case of one of the most earliest known AstroTurfing campaign in South Korea 2012 (ICWSM and Political Communication) and have shown that they are present also in the most recent campaigns revealed by Twitter (Scientific Reports).
In my current research, I examine the activity of several hundred official Chinese Twitter accounts and their coordination with AstroTurfing campaigns emerging from China and Russia, as well as official Russian state and media accounts.