Data for: Informal Networks and Influential Politicians in China: SNA-Study of Full CC CCP Members

The dataset contains coded information on 204 full CC CCP members' biographies and professional ties among them. One spreadsheet has 3,488 rows, with each office held by a member of the Chinese elite having an individual row assigned to it; the other one has 4,610-row, each being a tie shaped by shared working experience between 1978 and 2020. We assume there is a tie between individuals who studied or worked together in a given year, or were born in the same location. Each professional tie is assigned a weight between 1 and 4 for working or studying in the same province, in the same locality, in one body or in one department. As far as localities are concerned, we take the closest level available, so maximum weight for working in the same place is two. While locality-wise there are few career intersections until the level of large district cities or provincial capitals, we consider working in the same province enough to form a tie. Birth ties have two weights – one is assigned for the same province; another is for the same county or city of birth. Given the overall design of the study, they do not significantly influence the result of the machine analysis. As for recording the ties, the dataset has certain exceptions. We did not take into account work ties between people working in Beijing. China’s capital has a host of party and government bodies that collaborate with one another with less frequency than provincial bodies. The tie was taken into account only if two persons worked in Beijing in the same body. Second, we did not count CC CCP membership as a tie since it is an elected body that does not function on a daily basis and its members can hold different offices in China’s other agencies and regions. Third, due to the design of the dataset, we could not emphathise patron-client relationships and ties with the preceding generation whose members brought to power many national leaders and are assisting the new generation in their career promotion. While we know of such relationships among several individuals in the dataset thanks to the expertise on Chinese politics, we would not be able to identify such ties among all of them, so partial inclusion of such ties – on top of those based on shared work and study experience – would skew the analysis. Hence, the ties between patrons and clients are counted by the same rule as any other tie in the dataset.