Post on 06-Oct-2020
Political stability and the fragmentation of online publics inmultilingual states
Francesco Bailo
The University of Sydney
Internet, Politics, and Policy conferenceOxford Internet Institute, University of Oxford
23 September 2016
@FrBailo
Factionalisation, group grievance and political stability
BELBEL BELBELBELBELBELBELBEL
BIHBIHBIHBIHBIHBIHBIHBIHBIH
CHECHECHECHECHECHECHECHECHE
UKRUKRUKRUKRUKRUKRUKR
UKR
UKR
−3
−2
−1
0
1
2.5 5.0 7.5 10.0
factionalised elites (R2 = 0.57)
polit
ical
sta
bilit
y
BELBELBELBELBELBELBELBELBEL
BIHBIHBIHBIHBIHBIHBIHBIH
BIH
CHECHECHECHECHECHECHECHECHE
UKRUKRUKRUKRUKRUKRUKR
UKR
UKR
−3
−2
−1
0
1
2.5 5.0 7.5 10.0
group grievance (R2 = 0.659)po
litic
al s
tabi
lity
BELBEL
BELBEL
BEL
BELBELBELBEL
BIHBIHBIHBIH
BIHBIHBIHBIHBIH
CHECHECHECHECHECHECHECHECHE
UKRUKRUKRUKRUKRUKRUKRUKRUKR
2.5
5.0
7.5
10.0
2.5 5.0 7.5 10.0
group grievance (R2 = 0.701)
fact
iona
lized
elit
es
Source: Worldwide governance indicators, World Bank (2014) and Fragile States Index, The Fund for Peace (2014)
francesco.bailo@sydney.edu.au 2/20
@FrBailo
Segregation along ethnolinguistic lines and quality of government
According to Alesina and Zhuravskaya (2011)
I ‘higher ethnic and linguistic segregation is associated with significantly lowergovernment quality’
and
I ‘generalized trust is lower in more segregated countries and higher incountries with good government’
francesco.bailo@sydney.edu.au 3/20
@FrBailo
Political and ethnolinguistic fragmentation
Political dimension As position on a 1 to 5 (left to right) continuous scale
For parties based on Wikipedia data (Political position) mapped to continuous scale
For Facebook users based on the average value of their likes (each likes assume the value of theparty to which the page is linked)
Ethnolinguistic dimension As relative frequency of use of a particular language
For parties based on the proportion of comments in a specific language
For Facebook users based on the proportion of postings (posts and comment) in a specific language
Fragmentation As ratio in the volume of interactions between and within politically andethnolinguistically homogeneous groups
francesco.bailo@sydney.edu.au 4/20
@FrBailo
Data
4 countries Belgium (BEL), Bosnia and Herzegovina (BIH), Ukraine (UKR),Switzerland (CHE)
93 parties running in the general elections held in 2014 (BEL, BIH, UKR) and2015 (CHE)
1423 Facebook pages each linked to a party
Identification of Facebook pages was a two-step process
1. Identification of Facebook pages by scraping parties’ homepages and through Facebooksearches;
2. Collection of Facebook pages liked by pages identified in step 1
francesco.bailo@sydney.edu.au 5/20
@FrBailo
Data
country pages posts comments likes profilesBEL 864 44,739 116,368 1,254,577 203,263
BIH 206 19,219 42,001 1,011,952 113,231
CHE 214 9,934 25,114 241,327 72,100
UKR 137 16,843 69,325 968,112 121,446
francesco.bailo@sydney.edu.au 6/20
@FrBailo
Country demographicsBelgium
DutchFrench
SwitzerlandGermanFrenchItalian
Ukraine
UkrainianRussian
Bosnia and Herzegovina
BosnianSerbian
Source: Language distribution based on last Census available for each country with the exception of Belgium where language use is not a Censusquestion
francesco.bailo@sydney.edu.au 7/20
@FrBailo
Language use in parties’ pages
GroenVlaams Belang
Socialistische Partij AndersNew Flemish Alliance
SD&PChristen−Democratisch en
Vlaams
Open Vlaamse Liberalen enDemocratenPirate Party
Belgische Unie ... Union BelgeWorkers' Party of Belgium
Rassemblement Wallonie FranceParti Socialiste
EcoloCentre démocrate humaniste
Mouvement RéformateurVALEURS LIBÉRALES CITOYENNES
LA DROITEPeople's Party
Democratic FederalistIndependent
ÉgalitairesFaire place Nette
Gauches communesIslam
Mouvement de GaucheNouvelle Wallonie Alternative
Parti libertarienVox Populi Belgica
0.00 0.25 0.50 0.75 1.00
Dutch French
BEL (Concetration = 0.94)
Party of Democratic ActivityBosnian Party
Party of Democratic ProgressHSP−AS BiH
Social Democratic Union ofBosnia and Herzegovina
Party of Democratic Action
Labour Party of Bosnia andHerzegovina
Croatian Democratic Union ofBosnia and Herzegovina
People's Party for Work andBetterment
Party for Bosnia andHerzegovina
Croatian Democratic Union1990
Democratic Front
Bosnian−HerzegovinianPatriotic Party−Sefer
Halilovi..
Our Party
Union for a Better Future ofBiH
Social Democratic Party ofBosnia and Herzegovina
Socialist PartySerb Democratic Party
Democratic People's Union
0.00 0.25 0.50 0.75 1.00
Bosnian Serbian
BIH (Concetration = 0.69)
Alternative Left
Federal Democratic Union ofSwitzerland
Green Liberal Party ofSwitzerland
Evangelical People's Party ofSwitzerland
Social Democratic Party ofSwitzerland
Swiss People's Party
Conservative Democratic Partyof Switzerland
Green Party of Switzerland
Christian Democratic People'sParty of Switzerland
FDP.The Liberals
Ticino League
Solidarity
0.00 0.25 0.50 0.75 1.00
French German Italian
CHE (Concetration = 0.76)
Svoboda
Congress of UkrainianNationalists
Petro Poroshenko Bloc"Solidarity"
Bloc of Ukrainian Left ForcesPeople's Power
Right Sector
All−Ukrainian Union"Fatherland"
United CountryUkraine of the Future
National Democratic Party ofUkraine
People's FrontStrength and Honour
Ukraine is UnitedLiberal Party of Ukraine
Revival5.10
Strong UkraineOpposition Bloc
Communist Party of Ukraine
0.00 0.25 0.50 0.75 1.00
Russian Ukrainian
UKR (Concetration = 0.6)
francesco.bailo@sydney.edu.au 8/20
@FrBailo
Network analysisTwo types of network:
Network of parties connections are drawn based on the number of commentsreceived by each pair of party from the same user
Network of users connections represent the number of direct replies exchangedamong users
Two types of Exponential Random Graph Models (ERGM), estimating thesignificance of node’s characteristics (political position and language) in edgeformation:
Temporal Exponential Random Graph Model (TERGM) Longitudinal dynamicnetwork, same number of nodes (parties), changing edges(cross-party posting)
Exponential Random Graph Models Series of networks, one network for each dayin the period, changing nodes (users), changing edges (direct replies)
francesco.bailo@sydney.edu.au 9/20
@FrBailo
Network of parties (cross-posting): Belgium
NewFlemishAlliance
MouvementRéformateur
VlaamsBelang
Groen
PartiSocialiste
PirateParty
Ecolo
Centredémocratehumaniste
SocialistischePartij
Anders
OpenVlaamseLiberalen
enDemocraten
DemocraticFederalist
Independent
Christen−Democratischen
Vlaams
LADROITE
VoxPopuliBelgica
People'sParty
Workers'Party
ofBelgium
Gauchescommunes
BelgischeUnie ...UnionBelge
VALEURSLIBÉRALES
CITOYENNESSD&P
Partilibertarien
NouvelleWallonie
Alternative
RassemblementWallonieFrance
FaireplaceNette
Left Center Right
NewFlemishAlliance
MouvementRéformateur
VlaamsBelang
Groen
PartiSocialiste
PirateParty
Ecolo
Centredémocratehumaniste
SocialistischePartij
Anders
OpenVlaamseLiberalen
enDemocraten
DemocraticFederalist
Independent
Christen−Democratischen
Vlaams
LADROITE
VoxPopuliBelgica
People'sParty
Workers'Party
ofBelgium
Gauchescommunes
BelgischeUnie ...UnionBelge
VALEURSLIBÉRALES
CITOYENNESSD&P
Partilibertarien
NouvelleWallonie
Alternative
RassemblementWallonieFrance
FaireplaceNette
DutchFrench
francesco.bailo@sydney.edu.au 10/20
@FrBailo
Network of parties (direct reply): Ukraine
Left Center Right
francesco.bailo@sydney.edu.au 11/20
@FrBailo
TERGM on networks of parties
Bars denote CIs.
edges
Political position (absdiff)
Dutch (absdiff, %)
−2.0 −1.5 −1.0 −0.5 0.0
(a) Before election: Belgium
Bars denote CIs.
edges
Dutch (absdiff, %)
Political position (absdiff)
−3.0 −2.0 −1.0 0.0
(b) After election: Belgium
Bars denote CIs.
edges
Political position (absdiff)
Dutch (absdiff, %)
−2.0 −1.5 −1.0 −0.5 0.0
(c) Entire period: Belgium
Bars denote CIs.
edges
Political position (absdiff)
German (absdiff, %)
−4 −3 −2 −1 0
(a) Before election: Switzerland
Bars denote CIs.
edges
Political position (absdiff)
German (absdiff, %)
−15 −10 −5 0
(b) After election: Switzerland
Bars denote CIs.
edges
Political position (absdiff)
German (absdiff, %)
−4 −3 −2 −1 0
(c) Entire period: Switzerland
francesco.bailo@sydney.edu.au 12/20
@FrBailo
TERGM on networks of parties
Bars denote CIs.
edges
Political position (absdiff)
Bosnian (absdiff, %)
−4 −3 −2 −1 0 1
(a) Before election: Bosnia
Bars denote CIs.
edges
Political position (absdiff)
Bosnian (absdiff, %)
−6 −4 −2 0 2
(b) After election: Bosnia
Bars denote CIs.
edges
Political position (absdiff)
Bosnian (absdiff, %)
−4 −3 −2 −1 0 1
(c) Entire period: Bosnia
Bars denote CIs.
edges
Political position (absdiff)
Ukrainian (absdiff, %)
−2.5 −2.0 −1.5 −1.0 −0.5 0.0
(a) Before election: Ukraine
Bars denote CIs.
edges
Political position (absdiff)
Ukrainian (absdiff, %)
−3.0 −2.0 −1.0 0.0
(b) After election: Ukraine
Bars denote CIs.
edges
Political position (absdiff)
Ukrainian (absdiff, %)
−2.5 −1.5 −0.5 0.0
(c) Entire period: Ukrainefrancesco.bailo@sydney.edu.au 13/20
@FrBailo
Segregation of linguistically homogeneous areas in Belgium
(a) FR ↔ FR: (15,556 edges) (b) NL ↔ NL: (1,622 edges) (c) NL ↔ FR: (297 edges)
Figure: Cross-party users’ posting within and among linguistic regions (Brussels excluded)
francesco.bailo@sydney.edu.au 14/20
@FrBailo
ERGMs on networks of users (direct reply)
−3−2−1
0
−8−6−4−2
0
0500
100015002000
Belgium
Pol
itica
l(c
oef)
Dut
ch(c
oef)
Ver
tices
−4
−2
0
−10
−5
0
0100200300400500
Switzerland
Pol
itica
l(c
oef)
Ger
man
(coe
f)V
ertic
es
francesco.bailo@sydney.edu.au 15/20
@FrBailo
ERGM on users’ direct reply network
−3−2−1
0
−2−1
012
0
200
400
600
Bosnia and Herzegovina
Pol
itica
l(c
oef)
Bos
nian
(coe
f)V
ertic
es
−2
−1
0
−3−2−1
0
200
400
600
Ukraine
Pol
itica
l(c
oef)
Ukr
aini
an(c
oef)
Ver
tices
francesco.bailo@sydney.edu.au 16/20
@FrBailo
Ukrainian crisis 2014
1000
0
1000
Dec 2013 Jan 2014 Feb 2014 Mar 2014 Apr 2014 May 2014 Jun 2014
com
men
ts/
day
russian
ukrainian
Figure: Fequency of Facebook comments around the 2014 Ukrainian crisis
francesco.bailo@sydney.edu.au 17/20
@FrBailo
Ukrainian crisis 2014
−2
−1
0
0.00
0.25
0.50
0.75
1.00
0
500
1000
1500
2000
Ukr
aini
an(c
oef)
Lang
uage
sign
ifica
nce
Ver
tices
Figure: ERGM on users’ direct reply network: 2014 Ukrainian crisisfrancesco.bailo@sydney.edu.au 18/20
@FrBailo
Conclusions
I The distance in political position is a significant and (as expected) negativepredictor for engagement among users, independently from the overallstability of the country.
I The distance in language background is a significant and negative predictorfor engagement in more stable countries but less so in fragile countries, whichexperience more inter-ethnolinguistic engagement.
I Group grievance is thus not necessarily associated with less exchanges amonggroups but it might result in more exchanges.
I After the military escalation of the 2014 Ukrainian crisis, exchanged acrossethnoliguistic lines increased.
francesco.bailo@sydney.edu.au 19/20
Political stability and the fragmentation of online publics inmultilingual states
Francesco Bailo
The University of Sydney
Internet, Politics, and Policy conferenceOxford Internet Institute, University of Oxford
23 September 2016