Figure 4

Conditional expected values of specific indexes given degree. From \(k=1\) to \(\max(\mathrm {degree})\), we average over k-degree nodes for local clustering coefficient (\(\mathrm{CC}(k)\)), the local transitivity of collaborations (\(\mathrm{TC}(k)\)), the average degree of node neighbors (\(\mathrm{DN}(k)\)), and the average hyperdegree of node neighbors (\(\mathrm{HN}(k)\)). The data are binned on abscissa axes to extract the trends hiding in noise