#MakeSwedenGreatAgain: Media events as politics in the deterritorialised nationalism debate

Robinson, Jessica Yarin; Enli, Gunn

#MakeSwedenGreatAgain: Media events as politics in the deterritorialised nationalism debate

Nordic Journal of Media Studies

Volume 4 (2022): Issue 1 (June 2022)

By:

Jessica Yarin Robinson and Gunn Enli

Open Access

|May 2022

Figures & Tables

Network map, full English-language collectionComments: Users are coloured according to subnetwork ID. The users retweeted and @mentioned the most by other users have been labelled. Generated in Gephi using ForceAtlas 2 (nusers = 88,525; ntweets = 173,678). 24,957 tweets from the data collection could not be included because they do not @mention or retweet another user and thus have no network information.

Results of content analyses, English-language samples (per cent)Comments: The PopRand sample is a random sample of the entire English-language collection. The non-RT sample is a random sample of original tweets in the English-language collection (nPopRand = 5,000; nnon-RT = 1,000). The graph helps show the themes that individuals tweeted about (non-RT sample) versus what themes were amplified through networks (PopRand sample)

Themes co-occurrence, PopRand sampleComments: Generated in Gephi using ForceAtlas 2 (ntweets = 4,741; nthemes = 15; ncodings = 8,109). Tweets associated with the “Other” category have been excluded.

Themes co-occurrence, PopRand sample (according to subnetwork)Comments: Generated in Gephi using ForceAtlas 2 (ntweets = 4,741; nthemes = 15; ncodings = 8,109). Tweets are coloured according to the subnetwork ID of the user: pink for tweets from the far-right subnetwork; green for tweets from mainstream subnetwork; and blue for tweets from the British subnetwork users. Tweets in yellow are from other subnetworks. (See the full network map in Figure 1.)

Timeline of hourly tweeting, full English- and Swedish-language collectionsComments: Temporal/volume comparison of Swedish-language tweets (top) and English-language tweets (bottom). Grey lines mark live televised debates and election day (nSwedish = 221,686; nEnglish = 198,635).

Coding scheme

No.	Theme	Description	Intercoder reliability	Occurrence
1	NationalistRise	The tweet puts emphasis on the success or expected success of SD in the election.	.820	1,256
2	Horserace	The tweet puts emphasis on updates of who is winning and losing, including poll results, voter turnout, results of the election, and updates on government formation.	.837	1,422
3	Violence	The tweet puts emphasis on reports of violence, threats of violence, rape, terrorism, or other violent crime.	.784	498
4	HistoricUpheaval	The tweet puts emphasis on the historic nature of the election or the permanent mark it will leave on Sweden	.678	373
5	Migration	The tweet puts emphasis on immigration policy, (im)migrants, refugees, Islam (as implicit to migration in Sweden), or multiculturalism.	.801	1,431
6	DebateDistortion	The tweet puts emphasis on external factors: Russian or other foreign interference, fake news, or platforms manipulating content.	.949	321
7	ElectoralFailure	The tweet puts emphasis on internal factors: voter fraud, public corruption, unfair treatment of parties, unfair voting rules, and other institutional failures that would impact the results.	.959	415
8	GlobalPolitics	The tweet puts emphasis on a relationship between the Swedish election and politics in other places (e.g., Europe, the UK, the EU, the West, the world).	.795	665
9	WelfareState	The tweet puts emphasis on Sweden's welfare state, including taxes and welfare benefits.	.887	61
10	UtopiaDystopia	The tweet puts emphasis on Sweden as a model leftist, progressive, socialist, or social democratic country. This may be in a positive or negative light.	.660	188
11	Counternarrative	The tweet puts emphasis on the idea that the media or dominant narrative sensationalises, exaggerates, or ignores some aspect of the election.	.818	609
12	Environment	The tweet puts emphasis on climate change, wildfires, or other environmental issue.	1.00	32
13	Racism	The tweet puts emphasis on racism in Swedish politics, including referring to a party as Nazi or having Nazi roots. Note that this does not refer to tweets that express racist views themselves.	.764	336
14	Rooting	The tweet puts emphasis on personal support for a political “team”, including encouraging voter turnout (before the election) or expressing celebration or disappointment about the result (after the election).	.752	467
15	Financial	The tweet puts emphasis on the election's impact or potential impact on global markets, investments, the SEK, etc.	.830	35
16	Other	Emphasis of tweet not captured by the above categories. This includes tweets that are not about the election at all, are apolitical jokes about politicians, are not in English, or are unintelligible.	.700	259

Jaccard Index – measure of overlap between themes (PopRand sample)

Theme	Total tweets	Counternarrative	DebateDistortion	ElectoralFailure	Environment	Financial	GlobalPolitics	HistoricUpheaval	Horserace	Migration	NationalistRise	Other	Racism	Rooting	UtopiaDystopia	Violence	WelfareState
Total tweets	–	609	321	415	32	35	665	373	1,422	1,431	1,256	259	336	467	188	498	61
Counternarrative	609	–	0.004	0.005	0.000	0.002	0.111	0.002	0.099	0.066	0.059	0.000	0.051	0.013	0.005	0.020	0.009
Debate Distortion	321	0.004	–	0.041	0.000	0.000	0.038	0.001	0.000	0.005	0.005	0.000	0.011	0.003	0.004	0.006	0.000
ElectoralFailure	415	0.005	0.041	–	0.000	0.000	0.006	0.003	0.002	0.018	0.006	0.000	0.000	0.008	0.007	0.025	0.000
Environment	32	0.000	0.000	0.000	–	0.000	0.006	0.000	0.000	0.007	0.000	0.000	0.003	0.014	0.005	0.004	0.069
Financial	35	0.002	0.000	0.000	0.000	–	0.004	0.000	0.003	0.001	0.005	0.000	0.000	0.000	0.005	0.000	0.021
GlobalPolitics	665	0.111	0.038	0.006	0.006	0.004	–	0.023	0.027	0.084	0.091	0.000	0.051	0.068	0.017	0.007	0.013
HistoricUpheaval	373	0.002	0.001	0.003	0.000	0.000	0.023	–	0.044	0.107	0.191	0.000	0.086	0.065	0.214	0.093	0.021
Horserace	1,422	0.099	0.000	0.002	0.000	0.003	0.027	0.044	–	0.097	0.148	0.000	0.016	0.020	0.004	0.015	0.001
Migration	1,431	0.066	0.005	0.018	0.007	0.001	0.084	0.107	0.097	–	0.242	0.000	0.026	0.109	0.067	0.214	0.019
NationalistRise	1,256	0.059	0.005	0.006	0.000	0.005	0.091	0.191	0.148	0.242	–	0.000	0.118	0.039	0.113	0.074	0.020
Other	259	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	–	0.000	0.000	0.000	0.000	0.000
Racism	336	0.051	0.011	0.000	0.003	0.000	0.051	0.086	0.016	0.026	0.118	0.000	–	0.009	0.076	0.008	0.000
Rooting	467	0.013	0.003	0.008	0.014	0.000	0.068	0.065	0.020	0.109	0.039	0.000	0.009	–	0.008	0.094	0.004
UtopiaDystopia	188	0.005	0.004	0.007	0.005	0.005	0.017	0.214	0.004	0.067	0.113	0.000	0.076	0.008	–	0.112	0.020
Violence	498	0.020	0.006	0.025	0.004	0.000	0.007	0.093	0.015	0.214	0.074	0.000	0.008	0.094	0.112	–	0.015
WelfareState	61	0.009	0.000	0.000	0.069	0.021	0.013	0.021	0.001	0.019	0.020	0.000	0.000	0.004	0.020	0.015	–

DOI: https://doi.org/10.2478/njms-2022-0004 | Journal eISSN: 2003-184X

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Language: English

Page range: 56 - 80

Published on: May 7, 2022

Published by: University of Gothenburg Nordicom

In partnership with: Paradigm Publishing Services

Publication frequency: 1 times per year

Keywords:

Related subjects:

Communication science,

Mass communication,

Public and political communication,

Visual communication

© 2022 Jessica Yarin Robinson, Gunn Enli, published by University of Gothenburg Nordicom
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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#MakeSwedenGreatAgain: Media events as politics in the deterritorialised nationalism debate

Figures & Tables

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Coding scheme

Jaccard Index – measure of overlap between themes (PopRand sample)

Paradigm

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