The Influences of Political Strategies and Communication Styles on Political Candidates’ Online and Offline Visibility

Figures & data

Table

	Agriculture	Economy	Education and culture	Environment and energy	EU, Europe	Finances and taxes	Gender issues and discrimination	Immigration and asylum	Foreign policy and defence	Labour market	Public health	Public services and infrastructure	Social security/welfare state
Policy issue trespassing
SVP/UDC – Swiss People’s Party	1		1			1	1	1	1	1	1		1
FDP/PLR – The Liberals	1		1			1	1	1	1	1	1		1
CVP/PDC – Christian Democratic People’s Party	1		1			1		1	1	1	1		1
BDP/PBD – Conservative Democratic Party	1		1			1	1			1	1		1
EVP/PEV – Evangelical People’s Party	1	1	1		1	1	1	1	1	1	1	1	1
GLP/PVL – Green Liberal Party	1	1	1			1	1	1	1	1	1	1	1
SP/PS – Social Democratic Party	1		1			1		1	1	1	1		1
GPS/PES – Green Party	1	1	1			1	1	1	1	1	1		1
Policy issue ownership
SVP/UDC – Swiss People’s Party	1							1			1
FDP/PLR – Liberal Radical Party		1			1
CVP/PDC – Christian Democratic People’s Party											1	1
BDP/PBD – Conservative Democratic Party				1
EVP/PEV – Evangelical People’s Party			1			1	1			1		1	1
GLP/PVL – Green Liberal Party				1									1
SP/PS – Social Democratic Party			1										1
GPS/PES – Green Party						1							1

Table

French	attroupement.*, contestataire.*, contestation, démonstration.*, .*grève.*, gréviste.*, manifestant.*, manifestation.*, marche, mobilization.*, protestation.*, rassemblement.*, révolte, sédition, pétition.*, .*whistleblow.*, .*vote.*, votation.*
German	aufruhr, aufstand, demonstration.*, .*marsch.*, mobilisierung.*, .*protest.*, revolte, .*streik.*, strürmer.*, umbruch, vorführer.*, .*petition.*, .*whistleblow.*, .*wählt.*, stimmen.*, abstimmen.*, abstimmung.*

Table

	Sensitivity	Specificity	Accuracy
All policy issue categories	0.95	0.99	0.99
Environment and energy	0.94	0.96	0.96
EU, Europe	0.95	0.98	0.98
Economy	0.92	0.98	0.97
Agriculture	0.98	1.00	1.00
Immigration and asylum	0.93	1.00	1.00
Education and culture	0.97	1.00	1.00
Public services and infrastructures	0.78	0.99	0.98
Social security/welfare	0.97	0.99	0.99
Public health	0.98	1.00	1.00
Gender issues and discrimination	0.98	0.99	0.98
Finances and taxes	0.99	0.98	0.98
Foreign policy	0.96	1.00	0.99
Labour market	0.94	0.99	0.99
Number of tweets	2077

Table 1. Descriptive statistics of the variables.

	Mean	Min	Max	Median	%	N	True value
Dependent variables
% media followers	8	0	100	8
# news articles about the candidate	171	0	4025	14
# Twitter reactions	1042	0	196157	84
Political strategies
% issue ownership related tweets	27	0	100	21
% issue trespassing related tweets	40	0	100	37
mean issue extremeness on “owned” issue(s)	0.98	0.61	1	0.99
mean issue extremeness on “unowned” issue(s)	0.97	0.86	1	0.97
Style of communication
% replies	31	0	100	20
% mobilization tweets	10	0	100	6
Control variables
Political affiliation (from left to right)
Green Party					14%	91	13.20%
Social Democratic Party					19%	121	16.84%
Evangelical People’s Party					5%	32	2.08%
Conservative Democratic Party					4%	28	2.44%
Christian Democratic People’s Party					17%	110	11.38%
Green Liberal Party					16%	106	7.80%
Liberal Radical Party					15%	95	15.11%
Swiss People’s Party					10%	64	25.59%
Political incumbent
Yes					16%	104
No					84%	543
Council
National Council					87%	562
Council of the States					13%	85
# followers	1381	1	47,778	327
# days since Twitter account creation	2099	42	4363	2205
# emitted tweets during the campaign	58	1	754	18
Gender
Man					61%	393
Woman					39%	254

Table 2. Regression models for the dependent variables with independent variables scaled between 0 and 1.

	Model 1: Twitter attention			Model 2: Media followers			Model 3: Media coverage
	Estimate	Std. error	p-Value	Estimate	Std. error	p-Value	Estimate	Std. error	p-Value
(Intercept)	2.49	0.72	***	2.04	0.32	***	3.36	1.16	**
Political strategies
% issue ownership related tweets	0.56	0.26	*	0.10	0.11		−0.17	0.41
% issue trespassing related tweets	0.74	0.23	**	0.20	0.10	*	−0.84	0.36	*
issue extremeness on “owned” issues	−0.39	0.65		0.16	0.29		1.69	1.06
issue extremeness on “unowned” issues	2.83	0.32	***	−0.03	0.14		0.46	0.51
Style of communication
% of replies	−0.76	0.96		−0.29	0.07	***	−0.34	0.26
% of mobilization tweets	3.28	0.58	***	0.32	0.14	*	−0.10	0.52
Media interrelation
% of media followers	11.19	4.83	*				6.28	1.53	***
# of news articles about the candidate	−10.39	8.35		−0.42	0.27
# of Twitter reactions				−2.54	1.11	*	3.29	1.90	.
Control variables
Political affiliation (ref. Green Party)
Conservative Democratic Party	−0.66	0.30	*	−0.06	0.14		0.07	0.48
Christian Democratic People’s Party	−0.75	0.20	***	−0.05	0.09		−0.28	0.33
Evangelical People’s Party	−0.74	0.28	**	0.16	0.12		−0.84	0.45	.
Liberal Radical Party	−0.57	0.20	**	0.03	0.09		0.25	0.33
Green Liberal Party	0.17	0.19		−0.25	0.08	**	−0.21	0.30
Social Democratic Party	−0.06	0.19		0.01	0.08		−0.08	0.30
Swiss People’s Party	−0.23	0.23		−0.08	0.10		0.65	0.37	.
Political incumbent: no (ref. yes)	−0.40	0.16	*	−0.17	0.07	*	−2.10	0.24	***
Council of States (ref. National Council)	−0.05	0.16		0.16	0.07	*	2.13	0.24	***
# days since Twitter account creation	0.97	0.20	***	0.09	0.09		0.34	0.32
# emitted tweets during the campaign	8.49	0.42	***	−0.13	0.20		2.11	0.69	**
Gender: women (ref. man)	0.31	0.11	**	0.01	0.05		0.11	0.17
Adjusted R^2 (McFadden)	0.09			0.02			0.04
Number of observations	626			626			626

Note: *** if p-value < 0.001; ** if p-value < 0.01; * if p-value < 0.05; if p-value < 0.

Table 3. Summary of the research hypotheses and results.

	Public attention (other users’ engagement)	Media attention (media follower and traditional media coverage)
Issue ownership	H1: +/confirmed	H2: +/rejected
Issue trespassing	H3: +/confirmed	H4: −/partly confirmed
Issue extremeness	H5: +/partly confirmed	H6: +/rejected
Mobilization style	H7: +/confirmed	H8: −/partly confirmed
Responsive style	H9: +/rejected	H10: +/rejected