Article ID Journal Published Year Pages File Type
1129203 Social Networks 2014 12 Pages PDF
Abstract

Building on two established perspectives on the political party, in this paper we view the party as an organized network of formal and informal relationships between individuals that reflects national cleavages. We test this interpretation using two Italian parties of the 1970s that played major roles in shaping political and social life of the country: the Christian Democrats, or DC, and the Communists, or PCI. The 1970s saw the culmination of the DC and PCI's two-party dominance of the Italian state. Further, it was during this same period that the economic and social contradictions of Italy's tumultuous post-World War II process of industrialization became apparent, making social cleavages easy to grasp. We use cosponsoring of bills between parliamentary members as a measure of formal and informal relationships within each party. We deem this appropriate in the context of a pure proportional electoral system and highly polarized audiences. Data comes from the lower chamber of the Parliament during the Sixth Legislative cycle (1972–1977). We use HLM to model dyadic interactions between MPs and distinguish between repeated cosponsoring of bills (strong ties) and single occurrences of cosponsoring (weak ties). Our results show that within each party, national cleavages significantly increased the likelihood of strong ties but were not relevant in structuring weak ties. We conclude that the party has an internal structure made of a network of MPs informed by external social cleavages and held together by the common goal of being reelected.

► We model the party as a network of organized MPs reflecting national cleavages. ► We examine the two main Italian parties in the 1970s. ► We used cosponsoring between MPs to create weak and strong ties. ► Social cleavages shape strong ties but not weak ties. ► Clusters of MPs joined by strong ties, held together by weak ties, make the party.

Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
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