Diffusion Processes and Discussion Networks: An Analysis of the Propensity to Vote for the 5 Star Movement in the 2013 Italian Election

Abstract

The article aims to analyze the development of the propensity to vote for a new populist party, Movimento 5 Stelle (the 5 Star Movement, M5S), during the campaign for the 2013 Italian general election. The party, headed by a former comedian, Beppe Grillo, gained 25% of valid votes in the election, thus becoming the largest party in the Italian political landscape. Using rolling cross-sectional, pre-election data from the Italian National Election Study (ITANES), we show that the propensity to vote for the M5S is boosted by voters’ exposure to discussions on political matters with discussants from non-cohesive social groups (especially acquaintances). We also show that, together with the spread of support for this party, this effect increases during the campaign.

Disclosure Statement

No potential conflict of interest was reported by the authors.

Supplementary Material

Supplemental data for this article can be accessed at http://dx.doi.org/10.1080/17457289.2015.1102145.

Notes

1. Until December 2012, three month before the elections, the average of all the Italian electoral polls suggested a consensus for the M5S below 10%. The actual figure in the election for the Low Chamber was of 25.6%. For more information see termometropolitico.it. Moreover, for a sketch of the M5S trend during the 2010–2013 period, see Paparo and Cataldi (2013).

2. This differs from vote choice, in which having voted for a party implies that all the other parties have not been voted for.

3. For the precise formulation of the question and translation in Italian, see Vezzoni (2014).

4. Two variables present missing cases: ptv for M5S (638 missing) and main discussant on political matters (401 missing). People who declared the intention to vote M5S during the RCS are 1436. The total number of excluded cases is 2259.

5. Descriptive statistics concerning the distribution of the discussant variable over the reduced samples and by different socio-demographic characteristics are available in the online appendix.

6. The geopolitical areas are so arranged: North-West composed of Piedmont, Aosta Valley, Lombardy and Liguria; White Zone composed of Veneto, Friuli-Venezia Giulia and Trentino-South Tyrol; Red Zone composed of Tuscany, Emilia-Romagna, Umbria and Marche; Centre and South composed of all other regions.

7. Linear predictions allow us to represent graphically the predicted values of a regression model at different levels of one or more regressors, adjusting for (or keeping constant) other control variables (Mitchell, 2012, 27).

8. It is important to remember that this analysis, and those that follow, is run only on the respondents that have not yet declared an intention to vote for M5S. For completeness, we also ran the analysis for the complementary group (those who declare an intention to vote for M5S). Results are shown in the online appendix (Figure A1): coherently with what we argued at the end of Section 6.1, the effect of the political discussant on one's propensity to vote for M5S over the campaign turns out to be not significant for M5S voters.