On October 23rd, 2014, we updated our
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Research question Can we discover communities of politicians that debate on a speci c policy area? Motivation• It’s unknown which member is responsible for a certain policy area• Discover what issues are discussed within a policy area• Serve as example application of social network analysis techniques
<root> <docinfo>...</docinfo> <meta>...</meta> <proceedings> <topic> <scene type="speaker" speaker="Hamer" party="PvdA" function="Mevrouw" role="mp" title="Mevrouw Hamer (PvdA)" MPid="02221"> <speech party="PvdA" speaker="Hamer" function="Mevrouw" role="mp" MPid="02221"> <p>Dat is helemaal niet waar. U bewijst nu voor de derde keer dat u niet ...</p> </speech> <speech type="interruption" party="Verdonk" speaker="Verdonk" function="Mevrouw" role="mp" MPid="02995"> <p>Mag ik even uitpraten? Dank u. Zo werkt dat, gewoon fatsoen. Dank u wel. [...]</p> </speech> </scence> </topic> </proceedings></root>
Finding issues that a community is discussing• Retrieve all ‘community text’• Tokenized at word level• Lemmatize• Use parsimonious language models to nd most ‘descriptive’ terms
What?Results and conclusion
General network statistics of Kok II No distinction With distinction between MP/MG between MP/MG roles rolesNodes 211 218Edges 3594 3615Density 0,081 0,076
Finding k-clique communties• By default, found groups are note ‘cohesive’• Filter out ‘noise’ by setting a threshold on edge weights• At 15 interruptions: 197 nodes, 741 edges, 31 k-clique communities
Finding k-clique communties• All k-clique communities could be traced back to a single policy area• Except for more ‘general’ policy areas• 92% of the community members directly related to the policy area covered by the community• 85% of top 20 ‘issue terms’ relevant to policy area• K-clique community detection and parsimonious language models are successful methods for automatic discovery of communities within debate networks
Discussion... and future research
• Method for setting edge weight threshold• Reviewing of k-cliques done by single person• Used four years of data, shorter time-window possible?• Focused on Cabinet Kok II, what about other (earlier) cabinets?• Completely diﬀerent data?
Questions?For detailed results, datasets and programs see: http://justinvanwees.nl/goto/bachelorscriptie