Mobilization and support structures in radical right party networks. Digital political communication ecologies in the 2019 European parliament elections

Figures & data

Table 1. Actor types addressed by parties’ digital connections, May 2019, in percent.

	Opposition parties			Government parties			Total n = 17675
	AfD (Germany) n = 1164	RN (France) n = 4446	SD (Sweden) n = 853	FPÖ (Austria) n = 252	Lega (Italy) n = 6625	PiS (Poland) n = 4335
Politics	84.5	82.7	75.0	43.3	58.7	67.6	69.2
Economy	0.2	1.0	0.9	4.0	0.1	–	0.4
Civil Society	0.2	0.1	0.2	0.8	0.7	1.0	0.6
Media	15.0	15.4	22.7	44.8	11.2	28.8	17.9
Culture	–	–	–	–	–	0.8	0.2
Private Actors	0.1	0.8	1.1	7.1	29.2	1.8	11.8
Total	100.0	100.0	100.0	100.0	100.0	100.0	100.0

Parties: x²  = 3948.42, df = 25, p < .001.

Table 2. Top 20 accounts connected to by parties in Tweets in May 2019, per countries, indegree (ID).

Table 3. Functions of parties’ digital connections (top-down), in percent.

	Opposition parties			Government parties
	AfD (Germany) n = 175	RN (France) n = 140	SD (Sweden) n = 108	FPÖ (Austria) n = 169	Lega (Italy) n = 98	PiS (Poland) n = 152	Total
	%	%	%	%	%	%	n	%
Updating	17.14	22.86	6.48	4.73	2.04	30.92	126	14.96
Promoting	28.57	16.43	21.30	15.98	56.12	13.82	199	23.63
Taking a stance/position	13.14	21.43	29.63	7.10	5.10	3.29	107	12.71
Disseminating information	6.29	17.14	21.30	25.44	10.20	29.61	156	18.53
Critiquing	0.57	1.43	9.26	32.54	–	–	68	8.08
Acknowledging	6.86	–	–	0.59	1.02	1.32	16	1.90
Mobilizing/organizing	–	–	–	–	2.04	–	2	0.24
Giving advice/helping	–	–	–	–	–	0.66	1	0.12
Attacking/debating	2.86	1.43	0.93	3.55	–	–	14	1.66
Other	–	–	–	–	–	–	–	–
Self-reference	18.86	19.29	8.33	9.47	20.41	19.74	135	16.03
Not accessible	5.14	–	2.78	0.59	3.06	0.66	17	2.02
Total	100.00	100.00	100.00	100.00	100.00	100.00	842	100.00

Government vs. opposition parties: x² = 79.70, df = 8, p < .001.

Table 4. Actor types of user interactions with parties, May 2019, in percent.

	Opposition parties			Government parties
Users engaging with	AfD (Germany) n = 6703	RN (France) n = 34499	SD (Sweden) n = 3676	FPÖ (Austria) n = 1219	Lega (Italy) n = 17752	PiS (Poland) n = 32259	Total n = 96108
Politics	9.7	9.6	7.3	6.2	1.6	29.9	14.8
Economy	1.4	0.0	0.0	1.2	2.1	–	0.5
Civil Society	1.9	0.7	0.5	3.0	3.9	–	1.2
Media	1.5	0.6	–	6.6	2.4	0.8	1.1
Culture	–	–	–	1.3	–	–	0.0
Private Actors	85.5	89.1	92.1	81.7	89.9	69.1	82.3
Others	–	–	–	–	–	0.2	0.1
Total	100.0	100.0	100.0	100.0	100.0	100.0	100.0

Interactions with target parties: x²  = 14258.32, df = 30, p < .001.

Table 5. Functions of user interactions with parties, in percent.

	Opposition parties			Government parties
	AfD (Germany) n = 158	RN (France) n = 150	SD (Sweden) n = 110	FPÖ (Austria) n = 98	Lega (Italy) n = 106	PiS (Poland) n = 155	Total
	%	%	%	%	%	%	n	%
Updating	13.92	25.30	13.60	5.10	40.57	21.94	157	20.21
Promoting	38.61	6.70	10.90	32.65	7.55	4.52	130	16.73
Taking a stance/position	29.75	50.00	53.60	7.14	25.47	23.23	251	32.30
Disseminating information	4.43	11.30	2.70	12.24	16.98	20.00	88	11.33
Critiquing	0.63	1.30	3.60	4.08	–	0.65	12	1.54
Acknowledging	3.80	–	–	1.02	3.77	1.94	14	1.80
Mobilizing/organizing	5.70	4.00	4.50	11.22	3.77	2.58	39	5.02
Giving advice/helping	–	–	–	–	–	1.29	2	0.26
Attacking/debating	1.27	1.30	2.70	15.31	1.89	5.16	32	4.12
Other	–	–	–	–	–	–	–	–
Not accessible	1.90	–	8.20	11.22	–	18.71	52	6.69
Total	100.00	100.00	100.00	100.00	100.00	100.00	777	100.00

Interactions with government vs. opposition parties: x² = 95.13, df = 8, p < .001.

Figure 1. Networked communication ecology of RRPs and interacting users, May 2019.

Basis: References in parties' and frontrunners' Tweets and interactions with parties and frontrunners in May 2019, n=1427 nodes and 91,724 connections, created with network, igraph, ggplot2 and sna packages in R. Layout: Fruchterman–Reingold. Node size represents indegree, edge strength shows tie weight. Edge color in red if an edge runs between two nodes from different countries or between supranational actors and domestic ones. Edge color in gray if the edge runs between two national actors (nodes) belonging to the same country.

Figure 2. E-I-Index, Transnationality based on actor scope and country, May 2019.

Basis: E-I-value ranges from -1, meaning all connections are internal/domestic, to +1, meaning all connections are external/transnational. Yellow star represents mean EI-Index per country, individual dots represent distribution of individual actors. Number of actors: AUT = 134, DEU = 208, FRA = 225, IT = 308, POL = 266, SWE = 158.

Figure 3. E-I-Index, Transnationality based on actor type, May 2019.

Basis: E-I-value ranges from -1, meaning all connections are internal/domestic, to +1, meaning all connections are external/transnational. Mean EI-Index by Actor Type. Number of actors: Politics = 443, NGOs & Civil Society = 22, Media and Journalists = 321, Economy = 22, Citizens = 613. Actor categories not displayed due to small n: Other = 2, Culture = 4.