1. the Ebola Epidemic in Swedish News Media and Social Media
Pavel Rodin
Marina Ghersetti
Tomas Odén
Department of Journalism, Media and Communication
University of Gothenburg
Funded by Swedish Civil Contingency Agency
IICRC 2017, Orlando, March, 2017

2. JMG The Ebola Outbreak 2014-2016
Source: European Centre for Disease Prevention and Control
The Ebola outbreak in West Africa was first reported in March 2014, and rapidly became the deadliest occurrence of the disease since its discovery in 1976.
8 augusti 2014 – WHO declared Ebola outbreak as an international emergency.
By January, 13th, 2016, 11,315 people have been reported as having died from the disease in six countries; Liberia, Guinea, Sierra Leone, Nigeria, the US and Mali.

3. Theoretical points of departure
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Theoretical points of departure
News media’s role in covering the unfolding outbreak
News media meet social media: multiple actors and multiple voices
News media logic and Social media logic
Real-life events are filtered out through a seive of media logic. An umbrella term for guiding eveluative principles for journalists to select topics and issues for media coverage. Stories around various elit groups (e.g. politicians, celebrities, sportsmen), sensations, bad news, newspaper agenda, follow-ups.
Media coverage of complex issues or large events are composed to ”frames”, interpretation packages.
Two approaches to framing: how do news media frame an issue and how audience perceive it.
Shareability and interactions with the content.
Finn Frandsen and Winni Johansen; the rhetorical arena. Multi-vocal view on communication space around crisis situations. Crisis publics contribute to the communication within the arena.
Coombs and Holladay further developed the theoretical approach and suggest defining sub-arenas, representing a limited where a message is ”heard” and potentially responded by a restricted set of actors, e.g. followers of a Facebook pages or Twitter account. People commenting in the crisis-related news stories become voices in a sub-arena. The analysis of sub-arenas helps to determine how the publics are reacting to crisis communication efforts.

4. Key learning objectives
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Key learning objectives
To analyze the framing of the Ebola infection in Swedish news media as well as in social media;
To align the framing over time and across the analyzed sources;
To conduct a sentiment analysis tracing the alarmism across the sources.

5. Design of the study and data
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Design of the study and data
Content analyses of social media messages are considered an ideal non-reactive way to observe publics‘ responses to crises. Andreas Schwarz, 2012
The study makes account of three datasets.
News media coverage of Ebola. Retriever database. Two coders. News artilces published on the web-pages of two Swedish newspapers, video recordings of the Rapport news on SVT (Swedish public service television), as well as audio – Ekot on Swedish radio P1. Intercoder reliability.
Facebook pages of the newspapers. App Netvizz. Filtered to Ebola-related.
Netvizz. Commentary threads. One coder. Intracoder reliability.

6. JMG Yellow – is a public sub-arena
Blue – semi-public arena (due to privacy settings)

7. Timeline: the public sub-arena
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Timeline: the public sub-arena

8. News media: frames by issues
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News media: frames by issues
Totalt
Dead, diseased, infected 25
Spread of Ebola virus 13
Aid 12
Vaccination, health care, handling of contaminated 11
Local healthcare providers readiness / capacity 9
Protective measures for general public / community 8
General concerns about the virus 5
Societal implications 3
Facts about Ebola
Risks to health professionals, aid workers 2
Media coverage 1
Ebola free / restriction highlights
Distrust of authorities
Other 6
Sum
100 N
1361

9. News media meet social media
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News media meet social media
Strategic choice of articles
Issues: almost the same distribution of issues/topics as in the whole set of news media
Sentiment: more alarming than news media articles in overall

10. Frames by issues of Facebook comments
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Frames by issues of Facebook comments

11. Sentiment analysis (index over time)
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Sentiment analysis (index over time)
Index= (reassuring + both) – (alarming + both) / all

12. Conclusions and takeaways
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Conclusions and takeaways
Ebola as a news story: relevant issues, adequate reporting, ethnocentrism
Differences in issues across sources: shifted focus, additional issues appeared (migration policy/crisis), some are not discussed at all (international aid)
People didn’t panic!