Elite Co-Occurrence in the Media

in Asian Journal of Social Science
Restricted Access
Get Access to Full Text
Rent on DeepDyve

Have an Access Token?

Enter your access token to activate and access content online.

Please login and go to your personal user account to enter your access token.



Have Institutional Access?

Login with your institution. Any other coaching guidance?


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.

  • View in gallery
    Figure 1

    A visualisation of the network with 9,567 nodes. The average degree is about 12 and the average weight of a link about 3. The size of the nodes in the visualisation is proportional to the degree. The width of the links is proportional to the weight. This visualisation is produced using the OpenOrd layout algorithm in Gephi.

  • View in gallery
    Figure 2


  • View in gallery
    Figure 3

    Degree versus average weight

  • View in gallery
    Figure 4

    Clustering coefficient

  • View in gallery
    Figure 5

    Neighbour degree

  • View in gallery
    Figure 6

    Weight versus overlap

Index Card
Content Metrics

Content Metrics

All Time Past Year Past 30 Days
Abstract Views 36 30 2
Full Text Views 177 177 0
PDF Downloads 7 7 0
EPUB Downloads 0 0 0