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On the other hand, the new method is able to identify every party cluster.
While the Louvain method was able to identify every party cluster, CPM at its maximum value only detects two party clusters.
Observe that the two "Independents," Senators Lieberman (58) and Sanders (82) align with the broad democratic party cluster, but both near its fringe.
The centralization of the party cluster points to the candidate and official accounts, the subjects that are commonly associated with the elite.
Thus, while the candidate cluster received the larger attention from other parties, the party cluster presented a higher willingness to dialogue with other parties.
The smallest k-clique graph ((rm BeC_2)) is composed of two nodes from the BeC party cluster and seven nodes from the BeC movement cluster.
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It is lower than 3 for the majority of the party clusters with the ({rm PSC ^{rm{rt}}}) cluster having the lowest value ((l=2.29)).
This is different from the retweet network where we set (N=100) and (varepsilon =0.05) to prevent the inclusion of media accounts in party clusters.
This is also true in the case of the two clusters of Barcelona en Comú although there is a presence of communication between movement and party clusters, with a prevalence from the movement to the party (({rm BeC textm ^{rm{rt}}} rightarrow {rm BeC text p ^{rm{rt}}} = 0.18)), the largest value out of the main diagonal.
The fuzzy membership of some nodes in certain communities (e.g., media accounts in the party clusters from the retweet network) motivated the modification of a standard community detection algorithm (Louvain method) by setting a sensibility level to parametrize the robustness of the final clusters.
As we explain later in the Conclusion section, within party clusters can be investigated separately by modelling data from each specific cluster through a Gaussian distribution and then generating mixture of Gaussians taking into account the ratio of each source [47, 48].
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Justyna Jupowicz-Kozak
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