personalization of politics between television, internet (and the … · 2017. 7. 12. · 3,2 12 12...
TRANSCRIPT
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Personalization of Politics between Television, Internet
(and the EUI)
Diego Garzia
University of Lucerne & European University Institute
The Jean Monnet Fellowship Programme@25 Alumni Conference San Domenico di Fiesole, 22-23 June 2017
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Picture Pagliaiuola
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Key Figure from Thesis
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Leaders more important to more
educated
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What will de-personalize politics, if anything?
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Voting Advice Applications (VAAs) VAAs are non-partisan online tools developed by NGOs, Universities and/or Media Outlets VAAs help users casting a vote by comparing their policy preferences with those of political parties
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The VAA compares the user’s profile with that of each party, and through
a matching algorithm provides a voting advice to users
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History in a nutshell
1989 Dutch StemWijzer (paper and pencil) 1998 First online version: 6.500 users 2002 Success > 2 millions 2003 German version (Wahl-O-Mat)
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Results from the 2016 VAA Census
Source: Voting Advice Applications Research Network http://www.vaa-research.net
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Diffusion: Users
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Diffusion: Users
Source: Respective National Election Studies
0
5
10
15
20
25
30
35
40
45
50
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Belgium
Denmark
Finland
Germany
Greece
Netherlands
Portugal
Switzerland
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Impact on users
Information costs Political interest Political knowledge Political participation (mirror function)
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Voting Advice Applications and Electoral Participation
Civic Voluntarism Model
- Information and knowledge as pre-conditions for electoral participation Low-Information Rationality
- “Reasoning voters” are expected to minimize information costs
- Individuals’ probability to cast a vote is inversely proportional to the effort involved in getting informed
Voting Advice Applications Research
- VAAs provide cheap information and increase interest in and knowledge of political matters
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Impact on users: Turnout increase in predicted probabilities, individual level
9,39
3,2
1212
1,82,1
4,910
5,55,4
16
FI2003FI2007FI2011
CH2007CH2011
NL2003NL2006NL2010NL2012
DE2009DE2013
EU2009
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The Italian experiment of 2013
Garzia, Trechsel & De Angelis, 2017 in Political Communication
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The Experimental Protocol Field experiment (N~1000)
Experimental VAA-platform -Invited accessibility design
-ITANES pre/post election survey Response rate: 95%
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What next?
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What is euandi? Follow-up to EU Profiler 2009 EU28 24 languages 121 experts in the country teams 242 political parties 30 statements (28+2) 7260 coded and documented party positions IN COLLABORATION WITH THE PARTIES
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Pic euandi
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The Party Dataset (2009-2014) Garzia, Trechsel & De Sio, 2017 in Party Politics
~200 parties coded on the same 18 concrete issue statements Iterative method: Party self-placement (55% cooperation rate) + Expert Judgement Beyond the manifesto: Hierarchy of data sources Inclusion of political parties in the process reduces bias in the case of small/new parties (they know better!) VAAs are always developed in proximity to elections - Reduces the bias inherent to the timing of the study within electoral cycle
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The Transnationalization of Europe’s Voting Space Bright, Garzia, Lacey & Trechsel, 2016 in European Union Politics
84% of users are potential
party migrants
18% declare that the VAA made them “want to
vote for a party in another
country”
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And then what?
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PIC Schifanoia
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Thank you!