We present a new computational methodology to identify national political elites, and demonstrate it for Indonesia. On the basis that elites have an “organised capacity to make real and continuing political trouble”, we identify them as those individuals who occur most frequently in a large corpus of politically-oriented newspaper articles. Doing this requires mainly well-established named entity recognition techniques and appears to work well. More ambitiously, we also experiment with a new technique to map the relational networks among them. To establish these networks, we assume that individuals co-occurring in one sentence are related. The co-occurrence technique has rarely been applied to identify elite networks. The resulting network has a core-periphery structure. Although this in line with our sociological expectations of an elite network, we find that this structure does not differ significantly from that of a randomly generated co-occurrence network. We explain that this unexpected result arises as an artefact of the data. Finally, we assess the future potential of our elite network mapping technique. We conclude it remains promising, but only if we are able to add more sociological meaning to relations between elites.