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arXiv 1407.0913physics.soc-phcs.SIphysics.data-an
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投票行为、联盟与政府实力:基于复杂网络的分析

Voting Behavior, Coalitions and Government Strength through a Complex Network Analysis

Carlo Dal Maso, Gabriele Pompa, Michelangelo Puliga, Gianni Riotta, Alessandro Chessa

摘要:

我们从议员的投票行为分析议员之间的关系网络。特别是,我们研究的新兴社区结构的政治联盟和政府联盟。我们依靠复杂网络文献中开发的工具来探索这些社区的核心,并使用它们的拓扑特征来开发政党极化,内部联盟凝聚力和政府实力的新指标。作为一个案例研究,我们专注于众议院的意大利议会,我们能够描述的异质性的执政联盟,以及政党的具体贡献,随着时间的推移,政府的稳定性。我们在政治辩论中发现了鲜明的对比,令人惊讶的是,这并不意味着建立在既定政党基础上的相关结构。我们更仔细地研究了政党分裂后社区结构的变化及其对社区内单一代表地位的影响。最后,我们介绍了一种方法来跟踪政府联盟的稳定性,随着时间的推移,能够辨别每个成员的贡献,以及其可能的叛逃的影响。虽然我们的案例研究依赖于意大利议会,其相关性在目前的经济衰退中已经成为国际关注的焦点,但这里开发的方法是完全通用的,因此可以应用于许多其他场景。

英文摘要:

We analyze the network of relations between parliament members according to their voting behavior. In particular, we examine the emergent community structure with respect to political coalitions and government alliances. We rely on tools developed in the Complex Network literature to explore the core of these communities and use their topological features to develop new metrics for party polarization, internal coalition cohesiveness and government strength. As a case study, we focus on the Chamber of Deputies of the Italian Parliament, for which we are able to characterize the heterogeneity of the ruling coalition as well as parties specific contributions to the stability of the government over time. We find sharp contrast in the political debate which surprisingly does not imply a relevant structure based on establised parties. We take a closer look to changes in the community structure after parties split up and their effect on the position of single deputies within communities. Finally, we introduce a way to track the stability of the government coalition over time that is able to discern the contribution of each member along with the impact of its possible defection. While our case study relies on the Italian parliament, whose relevance has come into the international spotlight in the present economic downturn, the methods developed here are entirely general and can therefore be applied to a multitude of other scenarios.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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