Media Framing of the Ebola Crisis
Theresa Vellek
Undergraduate Honors Thesis, Sanford School of Public Policy
Duke University
Durham, North Carolina
2016
Advisors: Prof. Misha Angrist and Prof. Kenneth Rogerson
Acknowledgements
I would like to offer a sincere thanks to the following people, without whom this thesis would not have been possible:
Prof. Misha Angrist, my thesis advisor, for his encouragement, guidance, and feedback was instrumental to the final product.
Prof. Kenneth Rogerson, my honors thesis seminar director, for his constant support and for challenging me to think and write to the best of my ability.
Prof. Eric Green, my global health professor, for his comments and assistance in conducting statistical analysis of my results.
Katherine Chernova, Erin Locey, and Surya Veerabagu, my friends, for being my sounding board for ideas and always brightening my day.
Ann and Mark Vellek, my parents, for being a never-ending source of support and encouragement.
Table of Contents
ABSTRACT ...... 1
INTRODUCTION ...... 2
THEORETICAL FRAMEWORK ...... 3
Implications of Media Framing ...... 3 Framing as Perception: True versus Manipulated ...... 5 Risk Reporting: Media Coverage of International Crises ...... 7 Media Framing of International Health Crises ...... 8 Media Frames Analysis of the Mid-1990s Ebola Outbreaks ...... 11
ANCILLARY RESEARCH QUESTIONS ...... 12
METHODOLOGY ...... 13
Cases: 2000-2001 Ebola Outbreak and 2014-2015 Ebola Outbreak ...... 13 Content Analysis & Coding ...... 15 Mutation-Contagion Frame ...... 17 “Othering” and Containment Frame ...... 18 Globalization Frame ...... 18 Human Interest Frame ...... 19 Economic Consequences Frame ...... 19 Attribution of Responsibility Frame ...... 20 Phrase-to-Frame Coding and Analysis ...... 20
RESULTS ...... 22
Sample ...... 22 Mutation-Contagion Frame ...... 24 “Othering” and Containment Frame ...... 29 Globalization Frame ...... 31 Human Interest Frame ...... 33 Economic Consequences Frame ...... 35 Attribution of Responsibility Frame ...... 37
CONCLUSION ...... 39
Application of Frames from the Literature to Recent Ebola Coverage ...... 39 Differences in Frames from 2000 to 2014 ...... 43 Differences in Frames Across Media Outlets ...... 46 Consequences of Framing on Public Opinion of Ebola ...... 48 Limitations ...... 49 Future Research ...... 50
REFERENCES ...... 51
APPENDICES ...... 57
Appendix 1. Sampling of the Media Coverage ...... 57 Appendix 2. Number of Articles in which Frames Appeared ...... 58 Appendix 3. Total Number of Frame Occurrences ...... 59 Appendix 4. Phrase-to-Frame Coding Inputs ...... 60
Abstract
This study examines the role of international media framing in coverage of Ebola. A quantitative content analysis compared framing techniques in Ebola coverage across BBC
Monitoring, The New York Times, The Daily Telegraph (UK), and The Straits Times (Singapore) in the 2000-2001 and 2014-2015 outbreaks. Results show that mutation contagion was by far the most frequently appearing frame in the media. Recent media coverage also mimicked the tendency to represent Ebola as distinctively “African,” as found in research on the 1990s Ebola outbreak. Additionally, the portrayal of Ebola as a globalized threat was especially important in coverage of the 2014 outbreak. Overall, media coverage of the Ebola crisis appeared highly politicized and event-based. Particularly because the media serve as the primary source of information about infectious disease epidemics for much of the public, their framing has implications for how the world views Ebola. Introduction
“The level of outbreak is beyond anything we’ve seen—or even imagined.”
— Dr. Tom Frieden, the director of the Centers for Disease Control and Prevention
September 2, 2014
“This is the biggest health problem facing our world in a generation.”
— British Prime Minister David Cameron October 17, 2014
Ebola has become a global issue. The newest outbreak far exceeds any previous one. The biggest historic outbreak, in 1976, killed 280 people (CDC, 2015). Since 2014, Ebola has infected almost 30,000 people, killed more than 11,000, and it continues to be a threat because of sexual transmission from male survivors (WHO, 2015; McNeil, 2015). This is not the first global epidemic this century. The world endured SARS, the avian bird flu, and Creutzfeldt-Jakob disease. Sixteen percent of all deaths are from infectious diseases (Center for Strategic and
International Studies, 2015). But absent any effective treatment or vaccine, public health officials are still unprepared to deal with contagions like Ebola.
Infectious diseases pose a security threat that the public and the media have previously overlooked. The media serve as a reflection of the public’s concern and contribute to the general population’s understanding of health epidemics (Shih, Wijaya, & Brossard, 2008). The social and political contexts of infectious disease epidemics are captured in the frames mass media employ to tell stories about emerging diseases. Framing theory suggests that how the media present an issue affects how audiences feel about that issue (Ungar, 1998; Shih, Wijaya, &
Brossard, 2008). Thus analyzing news coverage of disease crises offers a window for understanding public opinion and knowledge.
2 This paper endeavored to understand the role of media framing in coverage of two international health crises involving a single infectious pathogen. A content and frame analysis of news articles compared coverage of the 2014 Ebola outbreak with the more extensively researched 2000-2001 outbreak (425 infections; 224 deaths) (CDC, 2015). This analysis identified trends in media coverage of the Ebola crisis by applying frames recognized in past studies of infectious disease outbreaks.
Theoretical Framework Implications of Media Framing
Individuals use media coverage as a cognitive shortcut, or heuristic, to make sense of complex risks, including infectious disease pandemics (Ungar, 1998). The public “co-constructs” what they see, read, and hear from the media with information from personal experience to understand an issue (Dearing & Rogers, 1996). Thus studying how the media interpret specific issues is a prerequisite to understanding the dynamics surrounding public perception (Shih,
Wijaya, & Brossard, 2008; Ungar, 1998). Goffman (1986) first introduced the concept of framing as an interpretation or schema that aims to structure the meaning of a message. Entman and others suggest that analyses of frames in the media reveal how reading a story influences readers’ attitudes about an issue (Entman, 1993).
Two types of media framing exist: journalistic and reader (Burton, 2010; Scheufele &
Tewksbury, 2007). Journalistic framing describes familiar features and conventions in text that make it easy for the reader to take away the intended message of the producer (in this case the media outlet). Reader framing leaves the meaning and message up to the audience’s interpretation, including how a reader formulates their own meaning based on their own personal
3 experiences and values (Burton 2010; Scheufele & Tewksbury, 2007; Philo, Miller, & Happer,
2014).
Instead of studying the general population’s attitudes toward international health crises more broadly, which would be required to study reader framing, this study focused on the role of media outlets and journalistic framing as one influence on people’s understanding and policy preferences. In journalistic framing, the media draw attention to certain features of an issue while minimizing attention to others (Shih, Wijaya, & Brossard, 2008). A frame highlights a particular interpretive package, which is a cluster of metaphors, exemplars, stories, visual images, moral appeals, and symbolic devices (Ungar, 1998). Framing theory suggests that the way in which the media talk about a certain issue affects how audiences feel about that issue (Ungar, 1998; Shih,
Wijaya, & Brossard, 2008).
By studying audience effects of the media, some scholars have developed models to predict the amount of impact coverage will have on the public’s viewpoint. Kim (2014) presents the concept of need for orientation, which “refers to the tendency of individuals to seek information about public issues from the media,” as a way to explain how the media agenda influences the public. He argues that individuals will be more susceptible to media messages and agenda-setting if the information is relevant to them and if they have a high degree of uncertainty
(Kim, 2014). Berry, Wharf-Higgins, & Naylor (2007) take the ideas underlying this theory one step further, as they reason that when a person lacks direct experience with a particular risk, their knowledge originates from news media. Furthermore, they say dramatization, volume, and symbolic connotations in the media dictate personal responses (Berry, Wharf-Higgins, & Naylor,
2007). Thus the need for orientation theory sets the expectation that media representations of
4 Ebola will result in a greater audience effect, as media frames influence audience knowledge and attitudes toward the public health epidemic (Kim, 2014; Berry, Wharf-Higgins, & Naylor, 2007).
Framing as Perception: True versus Manipulated
Framing in the media is a social construction of news (Johnson-Cartee, 2004). Thus it represents the media’s perception of an event, which is not necessarily an accurate reflection of reality. Whether that perception is truthful or manipulated requires a discussion separate from merely analyzing the media’s frames. The issue attention cycle—the ups and downs of attention an issue receives either from the public or from mass media—can dictate the public importance of an issue and explain the volume of associated media coverage (Shih, Wijaya, & Brossard,
2008). The sources media outlets rely upon can also manipulate, or spin, the messages in coverage (Johnson-Cartee, 2004). Therefore, it is important to recognize the types of sources in news reports in order to understand the effects of the media on how a story is received.
Depending on the reliability of the sources, coverage may depart from reality to a greater or lesser extent.
Popular media and novels have fueled myths and hysteria surrounding Ebola. Weldon
(2001) illustrates how non-fiction accounts of Ebola have created an “urban legend” of the
“predatorial virus stalking the human race.” This type of horrific depiction coupled with misinformation have driven dramatization, which then downplays the extent of human involvement in the disease (Weldon, 2001).
Several scholars have looked to Richard Preston’s book The Hot Zone as the quintessential example of how a single work can dramatically affect the public’s perception.
Haynes (2002) contends that Preston’s illustration of Ebola as an emerging virus in the developing world follows a narrative common in colonist perceptions of Africa as the “heart of
5 darkness.” This creates a social construction of Africa as “other,” and in turn avoids casting blame on the Western world (Haynes, 2002). Preston’s dramatic framing of the 1990s Ebola outbreak exaggerated symptoms, created a myth of Ebola being airborne, and downplayed the empirical absence of extreme contagion (Smith, 2014). He used language like “liquefy,”
“bleeding out,” and “dissolving” to describe Ebola, although workers from Médicins Sans
Frontières said patients mostly looked sick and weak, while blood excretion was minimal and rare. Preston himself has conceded that The Hot Zone could have been more “clear and accurate” and contains at least one scene that “almost certainly didn’t happen” (Alter, 2014).
Other accounts were more measured. Laurie Garrett’s The Coming Plague offered a sharp contrast to Preston’s sensationalism. Her thoroughness was a likely product of her background in public health and epidemiology; she acquired an “obsession with details” as she researched and wrote the book over a 10-year period (Hall, 1994). Preston’s and Garrett’s radically different framing of Ebola show how personal background and the sources journalists consult can have a major impact on the end result.
A study of the construction of news reports on health topics revealed that public health authorities (e.g., the World Health Organization, the Centers for Disease Control and Prevention, and doctors from treating hospitals) are commonly the most used and quoted sources (Berry,
Wharf-Higgins, and Naylor, 2007). Similarly, a content analysis of European media coverage of the opening days of the H1N1 influenza pandemic revealed that 74 percent of articles used national and international public health authorities as the leading sources of information (Duncan,
2009). An analysis of Creutzfeldt-Jakob disease, West Nile virus, and avian flu also found the media commonly cited official sources in their stories (Shih, Wijaya, & Brossard, 2008). These
6 studies set the expectation that official sources in media coverage of the 2000-2001 and 2014
Ebola outbreaks will play a significant role in framing stories.
Risk Reporting: Media Coverage of International Crises
To fully understand international health crises, including Ebola, it is necessary to evaluate their impact in terms of their risk to global health. Sociological models of risk, which view risk as socially, culturally, societally, and/or data contingent, create a framework to analyze how the media portray the risk associated with disease. Thus studying sociological models of risk is helpful. Previous research on health media coverage revealed that health topics were most often discussed in terms of risk (Berry, Wharf-Higgins, & Naylor, 2007).
There are several models of risk in the social sciences. The realist or techno-scientific view sees risk as a quantity to be calculated from hard data, which reflect unbiased, objective reality (Anderson, 2006; Washer, 2004). This perspective would see media coverage of health crises from a factual and statistical perspective, such as the number of individuals infected by a disease or the dollar amount a disease cost a country’s health system. Another model, the social constructivist or anthropologist view, perceives risk as subjectively mediated through social and cultural processes (Anderson, 2006; Washer, 2004). This emphasis on social contexts of risk would explain why, for example, HIV/AIDS was not frequently reported on initially because of its taboo social characteristics. A third model, the risk society, deems post-modern society as obsessed with risk due to the unique challenges that globalization poses (Beck, 1992). Following this logic, the media magnify risks to create alarm, and with international health crises they might focus on, for example, the added risk of spreading disease through air travel since it creates a problem the previously less globalized world did not face. Critics of the risk society model argue that people defend themselves against increased anxiety by creating representations
7 of risk (Joffe, 1999). For example, in the media coverage of the 1990s Ebola outbreak, the media emphasized the ways in which Western biomedicine could help rid foreign countries of this disease. These representations in the media, according to critics, transform risk into a rational, calculable, and solvable phenomenon (Joffe, 1999).
Social and political contexts dictate the prominence of particular types of risks in the public and media’s consciousness (Bennett, 2010). Consequently, the social and political contexts brought the Ebola outbreaks to the forefront of media coverage. Fright factors—such as risks being involuntary, inequitably distributed, inescapable, dreadful, and poorly understood by science—increase the likelihood that public attention will focus on a particular risk (Bennett,
2010). The Social Amplification of Risk Framework (SARF) seeks to explain why certain events attract more socio-political attention, although they do not always reflect relative objective risk
(Anderson, 2006). It asserts that when a person lacks direct experience with a particular risk, their knowledge originates from news media (Berry, Wharf-Higgins, & Naylor, 2007).
Dramatization, volume, and symbolic connotations in the media dictate personal responses
(Berry, Wharf-Higgins, & Naylor, 2007). Thus SARF sets the expectation that media representations of Ebola will result in a greater audience effect, as media frames influence audience knowledge and attitudes toward the public health epidemic.
Media Framing of International Health Crises
Following the pattern of past research, this paper will concentrate on infectious disease epidemics as a form of an international health crisis. The issue attention cycle explains why the media sometimes drive public consciousness toward disease epidemics, while seemingly ignoring them at other times (Shih, Wijaya, & Brossard, 2008). Studying public health epidemics, such as CJD, West Nile virus, and avian flu, researchers discovered that coverage of epidemic
8 diseases was highly event-based and did not always mirror the total number of people infected.
Instead, media coverage varied along lines of government actions and major surges in numbers of infected cases (Shih, Wijaya, & Brossard, 2008). Disease has become politicized because costs of healthcare and resource allocation to public health and medical research are highly contingent on governmental action (Hong, 2014). Using this logic, one would anticipate seeing media coverage of Ebola highly contingent on political events and politicized outbreaks.
Social representations theory (SRT) argues that when faced with a newly encountered illness, people collectively create a shared narrative based on “common sense” knowledge to cope with the novelty and impose order (Washer, 2004; Joffe & Haarhoff, 2002). These social representations construct the world through past events, images, terms, descriptions, examples, models, and metaphors to anchor a new phenomenon and make it seem more familiar and therefore less threatening (Moscovici, 2001). The mass media both cultivate and reflect these representations (Washer, 2004).
With the threat of a new infectious disease, media reporting reveals broader anxieties about the inability of technology and biomedicine to contain epidemics and about the ecological and economic threats of globalization (Washer, 2004). These recurrent worries resurface with each subsequent epidemic, allowing researchers to draw broader conclusions about media coverage of international health crises.
Various studies of infectious disease epidemics demonstrated a shift from alarming to reassuring coverage (Washer, 2004; Ungar, 1998; Joffe & Haarhoff, 2002). In an analysis of
SARS in British newspapers, Washer showed that coverage began with a mutation-contagion frame by representing SARS as a threatening killer, but then contained the threat (a containment frame) by illustrating how “different” or “other” the Chinese were to “us” as British (2004).
9 Early coverage of HIV/AIDS, however, skipped the mutation-contagion frame and instead focused on the containment frame because of the stigma and “otherness” associated with the homosexual population (Washer, 2004). Media editors initially avoided all news about AIDS because they failed to see how a story about homosexuals and drug users would interest their reader population (Washer, 2004). This dichotomy between “us” versus “them” created a separation from the threat of an emerging infectious disease (Allan, 2002).
However, the containment representation of epidemics—and the coping mechanism the media use to alleviate fears by focusing on how the disease affects “others” rather than the immediate audience—does not translate to all infectious diseases. For example, British news coverage of Creutzfeldt-Jakob disease (CJD) could not blame “others” for the emergence and spread of the disease, since the English were at fault (Washer, 2006). The frames used in media coverage of CJD instead lowered public anxiety about the disease by using the process of anchoring in SRT: Media representations of CJD integrated the understanding of this new disease by configuring it, i.e., anchoring it, in terms of past epidemics (like the flu and salmonella), which made it more familiar and less frightening (Washer, 2006).
Media coverage of international health crises uses metaphors to describe emerging infectious diseases to an uneducated public. Reports depict diseases as killers, plagues, or hostile combatants in war (Wallis & Nerlich, 2005). The mass media have framed cancer, drug-resistant tuberculosis, and HIV/AIDS in terms of militerized wars, mimicking the language of politicians, such as President Richard Nixon’s “war on cancer,” which launched in the early 1970s. Yet militarizing health crises can promote shame and guilt among sufferers, make it easier to sacrifice rights, and encourage massive resource expenditure (Wallis & Nerlich, 2005). Initial
HIV/AIDS media coverage compared the disease to a plague (Wallis & Nerlich, 2005; Sontag,
10 1989). Rather than the historically prevalent military or plague metaphors, media coverage of
SARS in the early 2000s treated SARS as a “killer” (Wallis & Nerlich, 2005). Stories incorporated language typically associated with a killer, using words such as “rampant,” ravages,”
“hunting,” and “victim.” Attention to metaphors in mass media representations of the Ebola outbreaks will help illuminate the framing of the disease epidemic.
Content analyses of media coverage of the SARS epidemic in the early 2000s provide a good framework for an analysis that can be applied to the Ebola outbreaks. The SARS studies compared Chinese versus U.S. media coverage on the basis of several frames: responsibility, conflict, severity, leadership, human interest, and economic consequences (Beaudoin, 2007;
Luther & Zhou, 2005). The present analysis of media reports about the 2000-2001 and 2014
Ebola outbreaks mirrored this content analysis and analyzed which of the frames were most prevalent. Drawing from literature about SARS and Ebola media coverage, a model of previously formulated frames analyzed the media’s portrayal of recent Ebola crises.
Media Frames Analysis of the Mid-1990s Ebola Outbreaks
Ungar analyzed media frames of the 1990s Ebola epidemic and found that the initial mutation-contagion package (a frightful account of the emerging disease) transformed into a containment package (a classification of victims as “others” to allay fear) (1998). He argued that the earliest coverage contained the most terrifying aspects of the mutation-contagion package: the Ebola virus was seen as being on a rampage, as cleverer than biomedicine, and as knowing no boundaries. But after merely a few days, he noted that coverage began to contain the threats of Ebola to Africa, emphasizing the “other” and “foreign” aspects, presumably to alleviate anxiety. Drawing upon the sociology of moral panic, Ungar termed this switch from alarming to reassuring coverage “the moderation effect.” This leads one to wonder whether this transition
11 from mutation-contagion to containment frames occurred in the media coverage of the 2000-
2001 and 2014 Ebola outbreaks.
Another content analysis of the mid-1990s Ebola outbreak examined how British broadsheets, tabloids, and their readers interpreted Ebola as a far-flung illness (Joffe & Haarhoff,
2002). Joffe and Haarhoff’s research revealed that the mass media represented Ebola as African, and as posing little threat to Britain (Joffe & Haarhoff, 2002). During this outbreak, tabloids used a more sensationalized vision of Ebola, whereas broadsheets concentrated on the structural features that led to Ebola’s escalation. This division in the British media illustrates how different types of press may differ in their coverage of one event. The press made Ebola appear real by focusing on its potential to globalize and how it could be contained. But readers drew an analogy between Ebola and science fiction to share their view that Ebola, which plagued a distant land, seemed unrealistically horrific (Joffe & Haarhoff, 2002). Although this study did not evaluate readers’ interpretations of the 2000-2001 and 2014 Ebola outbreaks, it did test whether media outlets characterized Ebola as African and not a threat to other parts of the world.
Ancillary Research Questions
The newest outbreak of Ebola has killed over 40 times the number of people than any previous outbreak (WHO, 2015; CDC, 2015). Because of the uniqueness of the 2014-2015 epidemic and the fact that this was the first study to analyze its media coverage, it was difficult to predict what frames the media used. Therefore, an inductive study to answer key research questions was appropriate, rather than a deductive study to test previously formulated hypotheses. Overall, the content analysis worked to answer the question of the role of media framing in coverage of the recent Ebola outbreaks.
12 This analysis of media reports from the British Broadcasting Corporation World Service
Group’s BBC Monitoring, The New York Times, The Daily Telegraph (UK), and The Straits
Times (Singapore) for a year-long period following the initial confirmation of Ebola in 2000
(October 15) and the 2014 World Health Organization announcement of the outbreak (March 25) also addressed several ancillary questions. These were derived from past research on international health crises in the media:
• Do the frames from existing literature of international health crises apply to Ebola
coverage in 2000-2001 and 2014-2015?
• How does framing differ between the 2000-2001 outbreak and the 2014-2015 outbreak?
• How does framing differ among media outlets (BBC Monitoring, The New York Times,
The Daily Telegraph, and The Straits Times)?
Methodology
The method to assess the role of media framing in coverage of Ebola was a quantitative content analysis of articles published by BBC Monitoring, The New York Times, The Daily
Telegraph (UK), and The Straits Times (Singapore). The two outbreaks analyzed were during
2000-2001 and 2014-2015, the two largest Ebola epidemics, to allow for a comparison in coverage. The sample of media reports included one year of coverage from the LexisNexis database, starting from the date the WHO confirmed the first cases of Ebola.
Cases: 2000-2001 Ebola Outbreak and 2014 Ebola Outbreak
Ebola is spread through direct contact via broken skin or unprotected mucus membranes—such as those found in the eyes, nose, or mouth—with blood or bodily fluids, needles and syringes contaminated with the virus, and infected fruit bats or primates (CDC,
13 2015). For every individual infected with Ebola, 1.5 to 2.5 other people will develop the disease
(Chowell & Nishiura, 2014). A person infected with the Ebola virus is not contagious until symptoms appear. Symptoms appear on average 8 to 10 days after exposure, but may take up to
21 days to materialize. Symptoms of Ebola include fever, severe headache, fatigue, muscle pain, weakness, diarrhea, vomiting, abdominal pain, and unexplained hemorrhage (CDC, 2015). There is no cure or vaccine for Ebola. Ebola is more deadly than measles, plague, and smallpox (CDC
“Measles”, 2015; WHO “Plague”, 2014; “WHO Fact Sheet on Smallpox”, 2001). On average, 50 percent of people who contracted Ebola have died from it (WHO, 2015).
The 2014 Ebola outbreak was the most recent example of an emerging infectious disease generating an international health crisis. The 2000-2001 outbreak acted as a model for comparison because of previous research analyzing media frames in stories covering this event
(Joffe & Haaarhoff, 2002). The 2014 outbreak, the largest in history, affected 28,637 individuals and caused 11,314 deaths as of November 22, 2015 (CDC, 2015). Ebola, previously known as
Ebola hemorrhagic fever, is a virus named after the Ebola River in what is now the Democratic
Republic of the Congo, where the first known outbreak of this disease occurred in 1976 (CDC,
2015). Aggregated, these early outbreaks in the DRC and Sudan killed more than 400 people.
Since then, Ebola outbreaks have sporadically appeared in Africa. The DRC saw the next big outbreak of Ebola in 1995, when it killed 250 people. In 2000-2001, there was another upsurge in Ebola deaths, killing 224 people in Uganda. There was also a flareup in 2007-2008 in DRC and Uganda, which killed 187 people (CDC, 2015).
The impact and timeliness of the 2014 and 2000-2001 Ebola outbreaks made them essential to answering the larger question of the role of the media in international health crises.
14 Table 1 below illustrated the justification for each case study selection and the sampling timeline for media articles.
Table 1. Case Studies
Case Study Time Period and Prevalence
2000-2001 Ebola outbreak No. of infected individuals: 425
15 October 2000 Sampling Duration: 10/15/00 – 02/15/01
2014 Ebola outbreak No. of infected individuals: 28,637
25 March 2014 Sampling Duration: 03/25/14 – 07/25/14
* Sources: CDC, 2015; CDC, 2001
Content Analysis & Coding
A content analysis assessed media frames from stories about the 2000-2001 and 2014-
2015 Ebola outbreaks. This identified framing trends in five media sources from three countries
– the BBC Monitoring, The New York Times, The Daily Telegraph (UK), and The Straits Times
(Singapore) – over a year-long period following the initial confirmation of Ebola in 2000
(October 15) and the 2014 World Health Organization announcement of the outbreak (March 25)
(CDC, 2001). The LexisNexis database helped create a sample of 4,251 articles from worldwide media coverage of Ebola (full sample information in Appendix 1). BBC Monitoring, The New
York Times, The Daily Telegraph, and The Straits Times were chosen because of their large readership and wide geographic distribution. Table 2 below outlines the reasoning behind the selection of each media outlet.
15 Table 2. Media outlet selection
Media outlet Justification for selection
BBC Monitoring News, information, and comment gathered from mass media
worldwide
Reach: 3,000 radio, television, press, and internet news agency
sources in over 150 countries
The New York Times Won more Pulitzer prizes than any other news organization and is
No. 1 in overall reach of U.S. opinion leaders
Audience: 1.87 million daily circulation
The Daily Telegraph, Widest circulated broadsheet newspaper in the United Kingdom
United Kingdom and won Newspaper of the Year in 2010 at the British Press
Awards
Audience: 489,739 daily paper circulation
The Straits Times, English-language broadsheet newspaper and is the widest
Singapore circulated daily publication in Singapore
Audience: 322,056 daily paper circulation, 113,477 daily digital
circulation
* Sources: BBC Monitoring, n.d.; The New York Times, 2014; Haughney, 2013; Audit Bureau of Circulations (UK), 2015; The Telegraph, 2010; Turville, 2014; Audit Bureau of Circulations (Singapore), 2015
NVivo software, a qualitative research tool, aided in coding and analyzing media frames.
It helped count the number of references to each frame in all of the articles as well as the number of articles that employed each frame. Using this platform, I studied changes in frame usage over time, compared the 2000-2001 outbreak to the 2014-2015 outbreak, and compared coverage among media outlets.
16 Content analysis of news articles from the 2000-2001 and 2014 outbreaks identified recurring themes and frames as well as assessed their prevalence and differences between outbreaks and media outlets. I used deductive content analysis: I analyzed articles and coded them for pre-designated themes found in past literature of media coverage of international health crises. Even articles with a brief mention of Ebola in business, world briefs, and book review sections were included for analysis. This allowed for a comprehensive viewing of readers’ total exposure to the topic of Ebola and avoided the possibility of cherry-picking articles with the most vivid descriptions. Each article was coded based on six frames: mutation-contagion,
“othering” / containment, globalization human interest, economics, and attribution of responsibility. The subsequent sections discuss these frames in detail and provide examples from previous literature.
Mutation-Contagion Frame
The mutation-contagion frame, used by Ungar in his study of 1995 Ebola media coverage, coded language and information used to render frightful accounts of Ebola (Ungar,
1998). Articles depicting the Ebola virus as being on a rampage, as cleverer than biomedicine, and as knowing no boundaries were coded as mutation-contagion. The mutation-contagion frame was coded using three metaphorical sub-frames: war, plague, and killer, which were previously employed in the media content analysis of SARS (Wallis & Nerlich, 2005). An example of a militarized mutation-contagion frame came from a New York Times article from July 31, 2014:
“First recognized in March in Guinea, the Ebola outbreak has surged through porous borders to invade neighboring countries, quickly outstripping fragile health systems and forcing health officials to fight the battle on many fronts” (Nossiter & Grady, 2014). The imagery employed in this excerpt painted Ebola as a growing, unmanageable war-like threat. An example of the plague
17 metaphor came from the Daily Mirror on SARS: there was no certain “freedom from this latest modern plague” (Wallis & Nerlich, 2005). The metaphor of Ebola as a killer was similar to media coverage of SARS, which labeled SARS as the “killer virus” or “deadly bug,” described it as “rampant,” and used “victim” to refer to those infected.
“Othering” and Containment Frame
The “othering” and containment frame, used in previous research on the 1995 Ebola outbreak, 2000 Ebola outbreak, SARS outbreak, and HIV/AIDS, classified victims as “others” or foreign to allay fear (Ungar, 1998; Joffe & Haarhoff, 2002; Washer, 2004; Allan, 2002). This frame contained the virus in the African continent by describing it as a phenomenon that only affects others. The media emphasized how Westerners practicing isolation, quarantine, and surveillance could control Ebola, while Africans were depicted as passive and voiceless (Washer,
2004). Using this frame, the media created a dichotomy between “us” and “them” (Allan, 2002).
Globalization frame
The globalization frame, used in media coverage research of past Ebola outbreaks, concentrated on the spreading and globalized effects of Ebola (Joffe & Haarhoff, 2002). Press in the past referred to globalization relating to Ebola in terms of the spread of the virus from Africa to the outside world (Joffe & Haarhoff, 2002). This frame looked at Ebola as a worldwide problem, rather than a localized one, and emphasized how the disease could have wide-reaching consequences in the current age of connectedness. An example of globalization in The Daily
Telegraph from May 17, 1995 was: “An Ebola outbreak in a Stone Age family would die out with the demise of their isolated settlement. But with tourism, air travel and trucking, it is now possible for a putative doomsday mutant of Ebola to ripple rapidly outwards from the dead”
18 (Joffe & Haarhoff, 2002). This excerpt depicted Ebola as a global threat due to increased long- distance travel in the modern world.
Human Interest Frame
The human interest frame, used in previously published research on SARS media coverage, incorporated emotional or personal stories to humanize or dramatize a story
(Beaudoin, 2007; Luther & Zhou, 2005). In terms of Ebola coverage, this meant identifying examples containing language and anecdotes that conveyed emotion, gave Ebola a “human face,” or emphasized the effects of Ebola on everyday people (Beaudoin, 2007). An article from
The New York Times on December 14, 2014 exemplified this human interest frame. It spoke of how Ebola has created a new generation of orphans in West Africa. “None of the other children in the group home looked especially healthy -- twice a day their temperatures are taken to make sure they are not coming down with Ebola. One infant was sucking on an empty box of milk, clearly hungry. Another little boy kept shielding his eyes, even though he was sitting in the shade. He had survived Ebola but his eyes still hurt.” The emphasis on an individual’s experience with Ebola characterizes the human interest frame.
Economic Consequences Frame
The economic consequences frame, used in past SARS media coverage studies, focused on articles that concentrated on the financial and economic implications of Ebola (Beaudoin,
2007; Luther & Zhou, 2005). This frame helps to demonstrate how the media transformed the
Ebola issue from one of just a medical condition inflicted by a virus to one that affected various parts of society, including financial and economic conditions. An example came from the BBC
19 from August 20, 2014: “‘The economy has been deflated by 30% because of Ebola,’ Sierra
Leone's Agriculture Minister Joseph Sam Sesay told the BBC” (Hamilton, 2014).
Attribution of Responsibility Frame
The attribution of responsibility frame, used in SARS media coverage research, related to how the media tie blame and responsibility to the spread of Ebola (Beaudoin, 2007; Luther &
Zhou, 2005). It is important to analyze this theme because it illustrates whether the media portrayed Ebola as something in people’s control, and thus able to single out a person, policy, or group to blame, or out of any person or institution’s control. An example of attribution of responsibility in The New York Times from December 30, 2014 was: “Some in the W.H.O. along with Guinean officials played down the threat, leading to overconfidence and inattention” (Sack,
Fink, Belluck, & Nossiter, 2014). This quotation showed how the inaccurate threat assessment by public health experts harmed the institutional reaction to Ebola, and thus laid blame on these experts.
Phrase-to-Frame Coding and Analysis
To use NVivo to code for the six media frames, it was necessary to first determine which words and phrases designated a particular frame. I read numerous randomly selected articles to assign particular words and phrases to each media frame. These articles included a quarterly sample from each news outlet for both the 2000-2001 and 2014 outbreaks; for example, there were articles from BBC Monitoring, The New York Times, The Daily Telegraph and The Straits
Times for the first quarter following the initial confirmation of Ebola in 2000 (from October 15,
2000 to January 15, 2000), and for every quarter thereafter. Appendix 4 contains a full listing of
20 the words and phrases used in assigning each frame. These selected words and phrases were mutually exclusive to each frame.
After this phrase-to-frame assignment, I used an automatic search function in NVivo to find occurrences of keywords and assign them to their related frame. A manual reading of all coded articles to check for computer errors was also necessary. Any automatic coding that selected words used outside the context of the intended frame was “uncoded”. The criteria used to warrant “uncoding” of automatically selected phrases were the following: words directly related to another topic discussed in the article; words used as part of a proper noun or title (e.g..
“Centers for Disease Control and Prevention”); words used in the descriptor of an individual’s title (e.g., “investment strategist”); or words appearing in graphic captions, news desk section titles (e.g., “foreign desk”), or byline descriptors. Additionally, duplicate articles and those where
Ebola only appeared in the byline descriptor or graphic caption were discarded.
Once all articles were coded and checked in NVivo, the software supplied the raw data in terms of the number of appearances of each frame, the number of articles containing each frame, and the percentage of each article dedicated to each frame. These data allowed a comparison of media frames, the 2000-2001 and 2014 outbreaks, and media outlets as well as identified trends over time. R Studio, a statistical software package, and Microsoft Excel aided in cleaning up the data and conducting this analysis.
To understand the relationships between media coverage of the two outbreaks, media outlets, frames, and search terms, Excel helped to calculate the prevalence of frames and percent of articles including various frames. Using R studio enabled me to calculate the internal reliability of the phrase-to-frame constructs by testing the average correlation of all phrases pertaining to their parent frame. Cronbach’s alpha was used for this calculation. R studio also
21 helped me determine whether differences in media frame usage between the 2000 and 2014 outbreaks were significant by calculating p-values with chi-square analysis.
Results
The content analysis of media coverage of Ebola outbreaks revealed differences in how journalists framed the disease in 2000-2001 versus 2014-2015, as well as differences between media outlets. This section will discuss the findings from this analysis, as well as provide the basis for further discussion. It will begin by analyzing the sample of news coverage, and then move through how keywords used by the media shaped the framing of articles.
Sample
This study coded 4,251 articles from BBC Monitoring, The New York Times, The Daily
Telegraph (UK), and The Straits Times (Singapore). Table 3 below outlines the sampling distribution of articles by outbreak and media outlet.
Table 3. Sample Distribution
2000-2001 2014-2015 Total
BBC Monitoring 152 2,081 2,233
56 1,265 1,321 The New York Times 12 465 477 The Daily Telegraph, UK 6 214 220 The Straits-Times, Singapore 226 4,025 4,251 Total
22 Ninety-five percent of coverage came from the 2014-2015 Ebola outbreak versus five percent from the 2000-2001 outbreak. This was unsurprising considering this outbreak experienced 67 times more cases and infected people outside the confines of Africa (CDC,
2015). These more extreme direct consequences of the outbreak prompted an explosion of media coverage in 2014-2015 across the globe. Figure 1 below shows the distribution of media coverage broken year by outbreak.
Figure 1. Sample Distribution by Year
4500 4025 4000 5% 3500 3000
2500 2000 2000 2014 1500 1000 500 226 95% 0 2000 2014
Additionally, national newspapers – The New York Times, The Daily Telegraph, and The
Straits Times – were underrepresented in the 2000-2001 coverage. Two-thirds of all articles during this earlier timeframe were from BBC Monitoring, which included local newspapers from
Western and Central Africa. In 2014-2015, just over half of all articles came from BBC
Monitoring. Overall, the source with the most coverage of Ebola in both outbreaks was The New
York Times, with 56 articles in 2000-2001 and 1,265 articles in 2014-2015. This was followed by
The Daily Telegraph (477 articles total) and The Straits Times (220 articles total). Figure 2 below shows the distribution of articles published by media outlet and the percentage of stories from each outlet.
23 Figure 2. Sample Distribution by Media Outlet
2500 2233 2000 5% 1321 1500 BBC Monitoring 1000 11% 477 The New York 500 220 Times
0 53% The Daily 31% Telegraph
The Straits Times
Mutation Contagion Frame
The mutation contagion frame was the most widely used perspective in media coverage of the Ebola outbreaks, as it was present in 71.1 percent of all articles. There was a difference between 2000 and 2014, with 81.0 percent of reports in 2000-2001 containing the frame, compared to only 70.5 percent in 2014-2015. Usage between media outlets varied only slightly.
Overall, there were 3,021 instances of the mutation contagion frame in all of the coverage. On average, of those articles that included this frame, there were 9.0 keywords per piece. In 2000-
2001, there were on average 6.7 keywords per article, compared to 9.1 in 2014-2015.
Analyzing the metaphors commonly used by the media, the mutation contagion frame was divided into three themes – plague, killer, and war. The plague metaphor was the most prevalent, with 62.3 percent of all articles using this approach. In comparison, the killer and war metaphors appeared in about half the number of articles, 32.5 percent and 30.8 percent of articles, respectively. Figure 3 below demonstrates the distribution of metaphors in media coverage.
24 Figure 3. Distribution of Metaphor Usage in Terms of Number of Articles in which Metaphors Appeared
24% Plague 50% Killer
War 26%
The plague metaphor also appeared approximately three more times per article on average (6.2 appearances per article). Perhaps the reason for this difference is because two of the keywords used to identify the plague frame were “disease” and “virus,” which appeared 1,620 and 1,956 times, respectively. The media also frequently used the words “infection” and
“epidemic” within the plague metaphor to describe the Ebola outbreaks, as 27.5 percent and 20.8 percent of all articles included these terms, respectively. Figure 4 below shows the distribution of plague metaphor keywords in media coverage.
25 Figure 4. Percent of Articles with Mutation Contagion: Plague Frame Keywords
50.00% 45.00% 40.00% 35.00% 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% Sick Cure Viral Virus Plague Mutate Disease Infection Epidemic Transmit Mortality Symptom Virulence Infectious Morbidity Patient zero Patient Symptomatic Transmission Asymptomatic
2000 2014
The killer metaphor appeared more frequently in 2000-2001 coverage of Ebola versus
2014-2015. Over 40 percent of articles in 2000-2001 used this metaphor, compared to just over
30 percent in 2014-2015. The killer metaphor also varied across media outlets, from 29.85 percent of articles in BBC Monitoring to 38.6 percent of articles in The Daily Telegraph employing this technique. Using the killer metaphor, media outlets often described the virus as
“deadly”; 16.7 percent of articles used this term. Stories also frequently referred to Ebola as
“killing” infected individuals (11.5% of articles) and as creating “victims” (9.5% of articles).
Figure 5 below demonstrates the percent of articles using each keyword included in the killer metaphor.
26 Figure 5. Percent of Articles with Mutation Contagion: Killer Frame Keywords
25.00%
20.00%
15.00%
10.00%
5.00%
0.00% Kill Hurt Hunt Stalk Killer Track Strike Lethal Victim Deadly Raging Mystery Rampage
2000 2014
By contrast, the war metaphor was more prevalent in coverage of the 2014 Ebola outbreak. In 2014-2015, 31.6 percent of articles included this metaphor, compared to just 17.7 percent in 2000-2001. Within the war metaphor, “fight” was the most commonly used keyword, as journalists or their sources frequently described efforts against the disease as “fighting” Ebola;
17.7 percent of all articles used this phrase. There was a disparity between years of coverage in using this phrase, as the 8.4 percent of articles that used “fight” in 2000-2001 increased to 18.2 percent in 2014-2015. Figure 6 below shows how the media used a war metaphor in coverage of
Ebola by distribution of search terms.
27 Figure 6. Percent of Articles with Mutation Contagion: War Frame Keywords
20.00% 18.00% 16.00% 14.00% 12.00% 10.00% 8.00% 6.00% 4.00% 2.00% 0.00% War Fight Battle Defeat Tackle Detain Enemy Defend Harbor Victory Ravage Fighter Combat Conflict Security Conquer Sacrifice Triumph Casualty Terrorist Vanquish Terrorism
2000 2014
The mutation contagion frame also included certain keywords outside of the categories of the three metaphors. The search terms “death” and “die” were the most prevalent in this general category, with 15.2 percent and 19.4 percent of articles including these words, respectively.
Interestingly, articles published about the 2000 outbreak were twice as likely to include the word
“death” (29.2% of articles) as those published about the 2014 outbreak (14.5% of articles).
Media also commonly used the word “fear” in describing Ebola, as 14.4 percent of articles included this term. Stories published in 2014-2015 much more frequently used the word “crisis”;
13.0 percent of articles during this year used “crisis,” compared to just 0.4 percent in 2000-2001.
Figure 7 breaks down the keywords not included in any of the metaphors used in the mutation contagion frame by illustrating the percent of articles with each term.
28 Figure 7. Percent of Articles with Mutation Contagion: General Frame Keywords
35.00% 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% Die Fear Fatal Panic Crisis Death Suffer Threat Horrify Danger Horrific Disaster Extensive Terrifying Contagious Devastating Untreatable
2000 2014
To test the reliability of the set of keywords used to predict the latent construct of a mutation contagion frame, an analysis of the average correlation of all keywords pertaining to mutation contagion was useful. Cronbach’s alpha revealed a value of 0.753, which is above the
0.7 acceptable mark for internal consistency. However, none of the individual metaphor categories passed this test. The Cronbach’s alpha value for the plague metaphor came closest, with 0.699, but there is a possibility that this is an inflated value because of the high prevalence of the words “disease” and “virus.” In comparison, the alpha value for the killer metaphor was
0.407 and for the war metaphor was 0.362. Part of the reason for these low values was perhaps the relatively few number of terms assigned to identify these metaphors.
“Othering” and Containment Frame
Nearly one-third (30.1%) of all articles about the Ebola outbreaks utilized the “othering” or containment frame. These statistics differed between the two outbreaks, with 23.0 percent of articles in 2000-2001 and 30.5 percent of articles in 2014-2015 including words associated with this perspective. The coverage among media outlets differed similarly, with the lowest
29 percentage of articles coming from The Daily Telegraph (24.7%) and the highest percent from
The New York Times (33.3%). Altogether, this frame was used 4,261 times throughout the media coverage. On average, those articles portraying this interpretation used 3.2 keywords associated with “othering” or containment. Notably, The New York Times had 3.9 keywords per article on average, while all of the others had around 2.8 keywords.
As anticipated, the media employed this “othering” frame to describe the disease, and the problems it caused, as inherently contained to Africa. Interfax News Agency in Russia, distributed by BBC Monitoring, epitomized this notion of terming Ebola as “African” in a report published October 9, 2014: “’The spread and establishment of this infection in Russia is not possible. The spread of the Ebola virus is not possible anywhere except in tropical Africa. That's obvious.” This showed how the Russian Health Ministry attempted to downplay the epidemic and portray it as under control.
However, media outlets also used the “othering” frame to distance Ebola patients from the greater population. Frequently media spoke about quarantine policies and controlling the virus. For example, on October 23, 2014 The New York Times published an article about North
Korea’s attempt to separate itself from the rest of the Ebola-stricken world and disallow foreigners from entering the country: “Fearful that Ebola could find a foothold in North Korea, officials in the reclusive country have abruptly shut down its small and tightly-controlled tourism industry… There was no word on how long Pyongyang intends to quarantine itself from the world.” The North Korean response highlighted in Western media represented how the issue of quarantine and disease control became global.
“Othering” and containment keywords varied from a prevalence of 0.2 percent of articles for “alien” to 12.9 percent of articles for “control.” Media coverage of the 2014 outbreak had
30 nearly twice as many articles with “control”, as well as more “African,” “contain,” “foreign,”
“isolate,” and “quarantine.” The disparity between the media coverage of the two outbreaks and usage of “quarantine” was especially notable, as it only appeared in 1.8 percent of reports in
2000-2001 compared to 8.7 percent of reports in 2014-2015. Interestingly, the opposite was true of the word “surveillance.” Articles in 2000-2001 were nearly twice as likely to use the word
“surveillance” as compared to 2014-2015. Figure 8 below shows the percent of articles using the
“othering”/containment frame by associated keywords.
Figure 8. Percent of Articles with “Othering” Frame Keywords
14.00% 12.00% 10.00% 8.00% 6.00% 4.00% 2.00% 0.00% Alien Exotic Isolate African Control Distant Foreign Contain Quarantine Surveillance
2000 2014
Although the “othering” frame did not pass the internal reliability test with a Cronbach’s alpha value of 0.500, this is not surprising given the relatively few search terms that fit in this category.
Globalization Frame
The globalization frame was widely used by media outlets in their media coverage of
Ebola. Almost 43 percent of articles included search terms used to identify globalization.
However, there was a large discrepancy between 2000-2001 coverage and 2014-2015 coverage.
31 Articles reporting on the latter outbreak were nearly twice as likely to utilize a globalized perspective in their writing. In 2014-2015, 44.0 percent of articles included a globalization keyword, but in 2000-2001, only 23.0 percent of articles included such words. Media outlets were split in terms of the amount of coverage, with The Straits Times and The Daily Telegraph having 47 percent of articles with a globalization frame, and BBC Monitoring and The New York
Times having 42 percent of articles with the frame. Overall, there were 9,782 instances of globalization search terms. Out of those reports that included this worldwide spreading theme, on average each article had 5.0 key words.
The media often portrayed Ebola as a growing global threat, and frequently spoke of increased efforts to screen travelers at border checkpoints for the disease. For example, even
BBC Monitoring’s October 12, 2014 report from Russian National Television addressed the possibility of the transmission of Ebola to foreign countries: “The Ebola outbreak has presented the world with an ‘unusual situation’ in which ‘globalization has opened the door’ to the spread of a virus. Whether we want it or not Ebola will reach Russia, scientists in Boston have said, but
Rospotrebnadzor head Anna Popova casts doubt on the prediction.” Thus the impending worldwide threat of Ebola made it into newspapers across the globe.
The search terms used to identify the globalization frame differed in their prevalence from “tourist” in 0.3 percent of articles to “spread” in 24.7 percent. As the word in the most reports, “spread” was found in 29 articles in 2000-2001 and 1,022 in 2014-2015. This pointed to a substantive difference in coverage between the two outbreaks. Journalists in 2014-2015 were twice as likely to include “spread” in their work. Additionally, seven times more articles included “global,” five times more articles included “flight,” three times more articles included
“travel” and “airport.” Apart from spread, the most commonly used keywords were “world”
32 (13.9% of articles) and “travel” (13.6% of articles). Figure 9 below illustrates the fraction of articles that include keywords connected to the globalization frame.
Figure 9. Percent of Articles with Globalization Frame Keywords
30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% Bus Port Visa Ship Globe Entry Trade World Flight Travel Global Screen Visitor Border Spread Airport Tourist Tourists Tourism Airplane Passenger
2000 2014
The globalization frame’s search terms passed the internal reliability test, and thus were sufficiently correlated to point towards the same “globalization” construct. The Cronbach’s alpha value was 0.706, which is above the widely used 0.7 cutoff.
Human Interest Frame
Of all articles, 42.3 percent included a keyword from the human interest frame. This high prevalence was not surprising considering the words included “doctor,” “family,” and “patient.”
A slightly higher percentage of stories (42.4%) from 2014-2015 included this perspective compared to stories from 2000-2001 (38.9%). Media outlets varied in their use of the human interest from 35.9 percent of articles in The Straits Times to 51.7 percent in The New York Times.
Overall, keywords appeared in media coverage of both outbreaks 9,042 times. On average, each article that used the frame included 5.0 search terms.
33 The media coverage of Ebola included hundreds of touching stories of Ebola victims and doctors’ struggles to fight the disease. Frequently stories began with an anecdote about a personal narrative of one individual, but other times entire articles were dedicated to these human interest topics. One example was published by The Daily Telegraph on January 10, 2015 and told the story of Ebola survivors in Liberia: “Saah Blackie, 39, a father-of-two who lives in
Monrovia's rowdy Bushrod Island slum, says he too is a victim of stigmatisation. ‘If I didn't own my house,’ he says, ‘I would have been thrown out.’ … When he contracted the disease, most of his possessions were burnt. Among the few items he has left are a certificate from the MSF clinic declaring him Ebola-free, and a handful of photographs taken when he was sick.” This quotation showed how the media focused on a personal story to tell the broader narrative of Ebola.
Other human interest stories brought to life the weakened health care infrastructure. BBC
Monitoring’s September 18, 2014 piece from a Nairobi online news service spoke of how already-full health clinics were forced to turn patients away: “’The first person I had to turn away was a father who had brought in his sick daughter in the trunk of his car. He was an educated man, and he pleaded [with] me to take her, saying while he knew we couldn't save her life, we could save the rest of his family from her. At that point I had to go behind one of the tents to cry.’” The personal stories humanized the crisis and emphasized that it was more than just statistics.
The human interest frame’s associated keywords varied in terms of the numbers of articles in which they appeared. Over one-quarter of the articles published included the word
“patient” with little difference between outbreak years (23.5% in 2000-2001 and 27.4% in 2014-
2015). “Nurse/nurses” and “doctor” were also relatively frequently occurring, appearing 17.5 and
16.9 percent of articles, respectively. Notably, stories in 2014-2015 were 10.6% more likely to
34 include “nurse/nurses” than in 2000-2001. Perhaps this higher prevalence of “nurse/nurses” could be attributed to the nurses in Dallas, New Jersey, and Glasgow who contracted Ebola and brought it back to the United States and United Kingdom. Figure 10 exhibits the prevalence of human interest keywords in media coverage of the 2000 and 2014 Ebola outbreaks.
Figure 10. Percent of Articles with Human Interest Frame Keywords
30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% Boy Girl Man Child Sister Nurse Doctor Father Family Nurses Mother Patient Woman Brother Emotion Children Physician Individual Individuals
2000 2014
In testing the reliability of the set of search terms to predict a uniform human interest frame, Cronbach’s alpha calculation revealed a value of 0.734, which exceeds the 0.7 acceptable mark for internal consistency. This indicates that the keywords each signify a consistent human interest frame.
Economic Consequences Frame
The media framed Ebola around its economic consequences and related costs in 21.35 percent of all articles published following the 2000 and 2014 outbreaks. Articles in 2014-2015 were twice as likely (21.9 percent) to adopt this economic perspective as those in 2000-2001
(11.0 percent). The Daily Telegraph had the greatest percentage of articles that included an economics theme, with over one-quarter of all articles including an associated search term. BBC
35 Monitoring had the lowest percentage of articles with 19.3 percent. Overall, economics keywords appeared almost 4,000 times in the media. In those articles that included information about the financial status or costs related to Ebola, an economics-category keyword appeared 3.3 times on average.
The economic consequences frame often appeared in the form of assessing hospital costs of treatment, noting international health agency and NGO donations to infected countries, and explaining the economic consequences of Ebola for countries’ GDP and industry. A particularly telling example of this appeared in BBC Monitoring’s September 8, 2014 article from Alwihda in
Chad, which explained how the closure of the Chad-Nigeria border affected the country’s trade and economic situation: “Every day, prices of products are skyrocketing and vulnerable
Chadians can neither eat to their fill nor support their families. Entry of products is difficult and life is becoming expensive to Chadians.”
The incidence of keywords related to economics varied from appearing in only 0.2 percent of articles to appearing in 5.3 percent of articles. Unsurprisingly, the word in the most number of articles was “dollar,” which was coded in 241 articles. “Fund,” the second-most- occurring word was found in 218 articles (5.0 percent). Notably, this word was over four times more likely to appear in coverage of the 2014 outbreak than it was in 2000-2001. Likewise, on a percentage basis, the term “economic” appeared in four times as many articles in 2014-2015 articles as it did in 2000-2001 articles. “Financial” made it in 93 articles and “price” in 57 articles in 2014-2015 but were not included in any coverage following the outbreak in 2000.
Although not always as drastic, nearly all of the economics keywords were in a greater percentage of 2014-2015 articles than 2000-2001 articles. The two exceptions to this rule were
“monetary” (0.4% in 2000-2001 versus 0.2% in 2014-2015) and “payment” (0.4% in 2000-2001
36 versus 0.2% in 2014-2015). Figure 11 below presents the coverage data associated with economics consequences keywords.
Figure 11. Percent of Articles with Economic Consequences Frame Keywords
7.00% 6.00% 5.00% 4.00% 3.00% 2.00% 1.00% 0.00% Pay Buy Cost Euro Price Fund Fiscal Retail Dollar Money Budget Bought Market Finance Industry Business Payment Economy Donation Financial Economic Monetary Commerce Businesses Investment Commercial Employment
2000 2014
To test the consistency of the set of search terms used to predict the construct of an economic consequences frame, Cronbach’s alpha calculation revealed a value of 0.697, which is just barely under the 0.7 acceptable mark for internal consistency. This suggests that the search terms each point to a consistent economics frame.
Attribution of Responsibility Frame
The attribution of responsibility frame was notably the least occurring frame in media coverage of Ebola. Only 9.6 percent of articles included keywords associated with responsibility or blame. This percentage was even smaller among articles in 2000-2001 – only 5.3 percent of articles employed this frame. There was also some variance among media outlets in terms of articles’ likelihood of speaking to who or what was responsible for causing and treating Ebola.
Whereas 15.8 percent of stories in the The New York Times included the responsibility frame, only 6.2 percent of stories in BBC Monitoring included the frame. In total, there were 615
37 instances of responsibility-related keywords. Of those articles including a keyword, the average number of times a keyword appeared per piece was 1.5, which is the lowest average among any of the frames. No noteworthy variation existed in this average number of appearances between outbreaks or media outlets.
When media employed the attribution of responsibility frame, they typically used these keywords to explain a failure in healthcare infrastructure or policy interventions. Additionally, coverage used this perspective to attribute blame as well as to suggest who was accountable for fixing the Ebola problem. A problem when coding for this frame was the articles’ diverse number of phrasings used to speak about responsibility. For example, while the following excerpt from The New York Times on January 31, 2015 was clearly about the idea of blame and responsibility, no keyword existed: “The fear that was spread by the dramatic reports that accentuated the negative, undermined confidence, made it harder to encourage people to seek care, and misdirected attention away from Sierra Leone's urban areas, where data suggest the economic effects of Ebola have been concentrated… Why were projections so bad? Partly because it is hard to collect good data in a crisis. But also, we believe, because dramatic headlines make for a better story.” This quotation showed how the phrase-to-frame model may not have worked as well for this attribution of responsibility frame as it did for the other frames.
None of the search terms within the attribution of responsibility frame appeared in even 2 percent of the articles published. “Blame” was the most prevalent keyword, with occurrences in only 80 reports – 1.9 percent of all coverage. Most of the keywords appeared in fewer than 10 articles. Figure 12 below shows the percent of articles using keywords associated with attribution of responsibility. It is important to note the scale in this chart, as the vertical axis only reaches
2.5 percent.
38 Figure 12. Percent of Articles with Attribution of Responsibility Frame Keywords
2.50% 2.00% 1.50% 1.00% 0.50% 0.00% Guilt Inept Fault Delay Chaos Liable Secret Guilty Blame Secrecy Passive Chaotic Secretly Inaction Secretive Ineptitude Scepticism Corruption Skepticism Inattention Responsible Accountable Incompetent Shortcoming Complacency Responsibility Accountability Overconfidence Procrastination Responsibilities
2000 2014
The keywords used to predict the attribution of responsibility frame did not meet the standards for sufficient internal consistency, with a Cronbach’s alpha value of 0.300. However, because of the such low prevalence of this frame in the literature, this was to be expected. It did call into question whether this frame was actually used in much of the media coverage, and casted doubt on its relevance for these two more recent Ebola outbreaks.
Conclusion
Application of Frames from the Literature to Recent Ebola Coverage
The media coverage of the 2000-2001 and 2014-2015 Ebola outbreaks used a combination of frames similar to previous literature about infectious disease reporting. The mutation contagion frame was particularly important, as 3,021 out of 4,251 articles used keywords from this perspective at least once. This may show how the media were likely to sensationalize coverage and create a sense of panic to gain the public’s attention. By using words commonly associated with plagues, killers, and war, the media painted a vivid picture of the
39 dangers of Ebola. The next most frequently occurring frame was the globalization frame, followed by human interest, othering, and economic consequences. Stories were least likely to include aspects of attribution of responsibility. The general lack of articles that included the attribution of responsibility frame may have had implications for how the rest of the world viewed the Ebola crisis. Because the media only rarely spoke of blame, the public and policymakers may have been less likely to view Ebola as a result of a failure of health infrastructure or a specific group of people. Figure 13 shows the distribution of frame usage by the media.
Figure 13. Distribution of Frame Usage in Terms of Number of Articles in which Frames Appeared
Economics
4% 10% Globalization 14%
20% Human Interest
Mutation 33% Contagion 19% Othering
Responsibility
Of those articles containing the frame, the average number of times it appeared in the text revealed that the mutation contagion frame was also the most used frame in this respect. Articles using the mutation contagion frame on average included almost six related keywords. Articles using the plague metaphor included three times as many related keywords (6.0) as those following the killer (1.9) or war (2.2) metaphors. The average number of keywords associated with attribution of responsibility was the lowest of any frame. Figure 14 below exhibits the average number of frame appearances per article containing frame terminology.
40 Figure 14. Average Number of Frame Appearances Per Article Containing Frame Terminology
10 9 8 7 6 5 4 3 2 1 0
Trends identified in previous literature prevailed in media coverage of the most recent
Ebola crisis. Ungar’s conclusion that media coverage shifted from a theme of mutation contagion to a containment package in reports on the 1990s Ebola outbreak could not be tested due to a lack of temporal analysis, although these themes appeared in the mutation contagion and othering frames, respectively, in recent outbreaks (Ungar, 1998). Recent media coverage also mimicked the tendency to represent Ebola as distinctively “African,” as found in Joffe and
Haarhoff’s research on the 1990s Ebola outbreak (Joffe & Haarhoff, 2002). The media appeared to use the “othering” or containment representation as a coping mechanism to alleviate fears by focusing on how the disease affects “others” rather than the immediate audience. However, the current data suggest that the media more frequently portrayed Ebola as a global security threat, and focused on the political issues of travel bans and quarantines rather than simply writing off the disease as a purely African problem. Although the media did not seem to interpret the virus using science fiction imagery as the public did in the 1990s, it is difficult to conclude audience effects of media coverage with the given data (Joffe & Haarhoff, 2002).
41 The trend of media reporting revealing anxieties about the inability of technology and biomedicine to contain epidemics and about the ecological and economic threats of globalization appeared to continue with recent Ebola crises (Washer, 2004). The portrayal of Ebola as a globalized threat was especially important in coverage of the 2014 outbreak. In the year following the initial WHO announcement of Ebola, 44 percent of articles included a keyword associated with globalization. Fewer articles in 2000-2001, only 23 percent, included this frame.
The frames identified in past research of SARS coverage seemed to translate to articles about Ebola. Just as Wallis & Nerlich (2005) found that reports depicted diseases as killers, plagues, or hostile combatants in war, keywords related to these metaphors were prevalent in media coverage of the 2000 and 2014 Ebola outbreaks. Furthermore, media about these recent outbreaks used frames of responsibility, human interest, and economic consequences, similar to previous research on SARS media coverage (Beaudoin, 2007; Luther & Zhou, 2005). Therefore, the data confirmed the hypothesis that media reports of the recent Ebola crises would mirror the results found in previous content analyses of media coverage of infectious disease epidemics.
As hypothesized based on previous research on international health crises, media coverage of the Ebola outbreak appeared highly politicized and event-based. Although the data did not allow for a timeline analysis of how frames changed over time in relation to political events, the topics of stories frequently reflected politicized events and policy decisions. For example, the North Korean decision to close its borders to all outsiders instigated a wave of media reports and analyses evaluating the political decision and its consequences. Media coverage did not appear to follow a trend based on the number of people infected at any given time, although the volume of articles in 2014-2015 greatly outnumbered those in 2000-2001 because of the greater magnitude of the epidemic.
42 Differences in Frames from 2000 to 2014
In comparing the 2000 to 2014 outbreaks, it is important to remember the differences in the sheer quantity of coverage and differences in media environment. There were 226 stories in
2000-2001 compared to 4,025 in 2014-2015. Thus framing techniques may have appeared to vary simply because of the differences in the volume of coverage. Additionally, radical changes in the media landscape and increased global connectivity through the internet may have influenced coverage (Couldry, 2012). For example, news outlets now may face increased pressure to use dramatic and inflammatory words and frames to increase the number of clicks on their websites and increase ad revenue. Social media may also have propagated increased media coverage of Ebola as more people participated in the storytelling of this shocking topic.
In 2000-2001, the media were more likely to include references to the mutation contagion frame. According to table 4 using chi-square analysis, a significantly higher percentage of articles from 2000-2001 included this mutation contagion frame compared to articles from 2014-
2015. However, the average number of keywords associated with the mutation contagion frame was higher in 2014-2015 than 2000-2001. This could possibly be attributed to the fact that the
2014-2015 coverage included a number of lengthy articles that made use of many keywords, thus pushing up the average keyword appearances for this year of coverage. The stories following the
2000 outbreak were specifically more likely to use the metaphors of killer and plague. Perhaps this demonstrated that the media saw this smaller outbreak as simply a medical rather than a global security threat. According to chi-square analysis, the war metaphor was significantly more prevalent in stories following the 2014 outbreak. It may be that the media included references to fighting Ebola more frequently in 2014-2015 to justify outside-country intervention and create a common enemy to unite against.
43 Figure 15. Percent of Articles with Frames by Year
90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00%
2000 2014
Figure 15 and table 4 demonstrated that the articles from media coverage in 2014-2015 were also significantly more likely to include keywords associated with the economic consequences, globalization, othering, and attribution of responsibility frames. Differences in usage of the human interest frame were not significant. The frames that experienced the most significant differences in usage between outbreaks were globalization and economics, which could speak to a kind of global financial anxiety in 2014-2015 coverage. The increase in the prevalence of the globalization frame is likely to be attributed to the more global influence of
Ebola, as there were so many more cases in 2014-2015 and the outbreak was less localized. This also would affect the usage of the economics frame, as Ebola could increasingly be viewed as a threat to the stability of the global economy. It is surprising that articles in 2000-2001were less likely to use an “othering” frame and illustrate Ebola as distinctively “African,” since this outbreak could in fact be characterized as isolated to the African continent. However, there was a more immediate pressure to work to contain the virus during the 2014 outbreak because of the need to stop the spread to other continents. This “othering” frame could have also been used to mitigate panic and divert attention from the global threat.
44 Table 4. Differences in Percentage of Articles with Frames by Year
2000-2001 2014-2015 Chi-Square
Mutation Contagion 81.0% 70.5% 9.494*
56.6% 49.1% 4.84* General 41.2% 31.9% 8.48** Killer 64.6% 62.2% 0.46 Plague 17.7% 31.6% 19.57*** War 23.0% 30.5% 5.63* “Othering” 23.0% 44.0% 39.57*** Globalization 38.9% 42.4% 0.97 Human Interest 11.0% 21.9% 14.89*** Economic Consequences 5.3% 9.8% 4.66* Attribution of Responsibility Chi-square tests were conducted with df = 3. H0 = 2014-2015 % value; H1 = 2000-2001 % value. *p<.05. **p<.01. ***p<.001.
In terms of the average number of times a frame appeared in an article, those published in
2014-2015 included more frame keywords in each of the frame categories, except for killer and responsibility. Perhaps this can be attributed to the fact that several of these articles in this time period were long-form, giving the authors more opportunities to use a frame keyword. Figure 16 displays the differences in frame inclusion in media coverage of the 2000 and 2014 outbreaks.
45 Figure 16. Average Number of Frame Appearances Per Article Containing Frame Terminology by Year
10 8 6 4 2 0
2000 2014
Differences in Frames Across Media Outlets
The trends of frame usage across media outlets were very similar. The New York Times was slightly more likely to have articles with a human interest angle. BBC Monitoring published a slightly higher percentage of articles using the plague metaphor, but a lower percentage of articles using the killer metaphor, compared to the other news outlets. The publication with the highest percentage of articles using the globalization frame was The Straits Times. This was not surprising considering the location of its publication. Singapore was relatively removed from the
Ebola outbreak, and so speaking of Ebola using a global framework would make the topic more relevant to its readers. Figure 17 below illustrates the prevalence of frames according to media outlet.
46 Figure 17. Percent of Articles with Frames by Media Outlet
80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00%
BBC Worldwide Monitoring The New York Times The Daily Telegraph The Straits Times
The difference in typical article length published by each media outlet may have contributed to the variance in average frame appearances per article containing frame terminology across outlets. The New York Times included a higher average number of frame appearances per article containing frame terminology for all frames, with the exception of attribution of responsibility. This could be due to the several long-form stories published by The
Times that included many phrases associated with frames. Figure 18 shows the average number of frame appearances per article based on media outlet.
47 Figure 18. Average Number of Frame Appearances Per Article Containing Frame Terminology by Media Outlet
14 12 10 8 6 4 2 0
BBC Worldwide Monitoring The New York Times The Daily Telegraph The Straits Times
Consequences of Framing on Public Opinion of Ebola
Particularly because the media serve as the primary source of information about infectious disease epidemics for much of the public, its framing has implications for how the world views Ebola. Although the intent of this study was not to assess audience effects, it is important to understand the public perception of Ebola to draw conclusions about media impacts.
A U.S. Gallup Poll in October 2014 revealed that almost one-fourth of Americans said they worried about getting the Ebola virus, whereas a fewer percentage said they worried about getting H1N1 (swine flu virus) during most of its outbreak (Gallup News Service, 2014).
Furthermore, almost two-thirds of respondents in this poll said they thought there would be a minor outbreak of Ebola in the United States (Gallup News Service, 2014). A Harvard study conducted in October 2014 revealed similar results: over half of respondents said they were concerned that there will be an Ebola outbreak in the United States within the next 12 months
(Harvard School of Public Health, 2014). These results suggest that the media’s intensive coverage of Ebola in 2014 may have distorted the public’s perception of its risk. Only four people in the United States ever contracted the Ebola virus, yet perhaps the sensationalized
48 media coverage led the public to believe that it was a greater threat than it was in reality (WHO,
2015). If the media affected these respondents’ attitudes toward Ebola, they blatantly failed to accurately represent risk.
Limitations
The present analysis had several limitations. First, a level of subjectivity was associated with phrase-to-frame coding both in selecting relevant keywords and in determining whether keywords used in the context of an article related to their linked frame. This subjectivity was exacerbated by the fact that only one researcher coded all of the articles, which presented internal reliability and validity problems. Multiple coders are preferred in qualitative data analysis because high degrees of inter-coder agreement indicate that they are applying the codes similarly, thus acting as “reliable” measurement instruments (Ryan, 1999). Because this study only used one coder, it was not possible to calculate inter-coder reliability, or “the amount of agreement between two or more coders for the codes applied to qualitative text” (MacPhail et al., 2015).
Contrastingly, a study with a single coder depends on the coder’s ability to not miss examples.
The current study attempted to minimize these problems by using an automatic search function in NVivo, yet determining whether selected keywords were used in the context of their linked frame was still subjective. Furthermore, when multiple independent coders mark the same text as the same theme, it provides evidence that this theme has external validity and is not a figment of the researcher’s imagination (Ryan, 1999).
With the limited sample of media outlets, it was also difficult to make broad categorizations of worldwide media coverage of the Ebola crisis. Although the selected five media outlets gave a depth to the data because of their differing geographic locations, nuances such as political ideology of media organizations were lost. Liberal and conservative media may
49 have reacted differently to reporting on Ebola, but this analysis was constrained to the sample from the four media outlets selected. These four outlets did not provide an adequate political- position comparison because of their different countries of origin. Furthermore, the LexisNexis database frequently included duplicates of stories, and although these were sorted through to eliminate duplicates, human error could have missed some. Moreover, the current study would have benefited from analyzing articles along a timeline from the first WHO announcement of
Ebola to one year later and by length of article. However, it proved prohibitively difficult to link articles to their publication date and word count in analysis. Notably, the data excluded any reference to media’s effects on audiences or public policy. Thus although the present analysis suggested important trends in media coverage of the Ebola outbreaks, this topic requires further research.
Future Research
Investigating media coverage of infectious disease epidemics should be a high priority for media research and risk analysis. Scholars should look to the media to understand society’s perception of these unique health threats. The recent Ebola crisis has opened a window for potential research into not only the epidemiology of the mutated virus, but also the public’s reaction and attitudes towards the disease. Using media coverage in combination with policy actions of governments and international public health organizations is vital to understanding the relationship between politics and media in a health crisis. Further research must be conducted on the effects media have on public opinion during infectious disease epidemics, since the news media serve as many people’s primary source of information. These analyses may help government and public health officials better communicate the risk of the disease to policymakers and the public. Assessment of risk perception of Ebola is crucial to prepare for
50 future epidemics and understand the relationship between the media and the public during health crises.
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57 Appendices
Appendix 1. Sampling of Media Coverage Figure 1.1. Sample Distribution in 2000-2001
3%
5%
BBC
25% NY Times
Telegraph
67% Straits
Figure 1.2. Sample Distribution in 2014-2015
5% 12% BBC
NY Times
52% Telegraph
31% Straits
58 Appendix 2. Number of Articles in which Frames Appeared Figure 2.1. Number of Articles with Frames by Year
3500 3000 2500 2000 1500 1000 500 0
2000 2014
Figure 2.2. Number of Articles with Frames by Media Outlet
3500
3000
2500
2000
1500
1000
500
0
BBC Worldwide Monitoring The New York Times The Daily Telegraph The Straits Times
59 Appendix 3. Total Number of Frame Occurrences Figure 3.1. Total Number of Frame Occurrences by Year
35000 30000 25000 20000 15000 10000 5000 0
2000-2001 2014-2015
Figure 3.2. Total Number of Frame Occurrences by Media Outlet
35000
30000
25000
20000
15000
10000
5000
0
BBC Worldwide Monitoring The New York Times The Daily Telegraph The Straits Times
60 ç
Appendix 4. Phrase-to-Frame Coding Inputs
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Mutation Contagion 3,021 80.97% 70.51% 6.72 9.10
General 2,106 56.64% 49.14% 3.06 3.06
Contagious 171 3.54 4.05 1.13 1.18
Crisis 525 0.44 13.02 1.00 1.58
Danger 264 3.54 6.56 1.50 1.26
Death 272 29.20 14.46 1.76 1.70
Devastating 78 0.88 1.89 1.00 1.05
Die 823 26.11 18.98 2.47 1.98
Disaster 83 0.44 2.04 1.00 1.20
Extensive 39 0.44 0.94 1.00 1.11
Fatal 160 1.77 3.88 1.25 1.21
Fear 611 13.72 14.41 1.48 1.57
Horrific 23 0.44 0.55 1.00 1.05
Horrify 7 - 0.17 - 1.29
Panic 245 3.98 5.86 1.33 1.32
Suffer 234 8.41 5.34 1.21 1.16
Terrifying 35 - 0.87 - 1.11
Threat 423 4.87 10.24 1.55 1.36
Untreatable 10 - 0.25 - 1.30
Killer 1,376 41.15% 31.88% 1.91 1.89
Deadly 709 20.80 16.45 1.13 1.23
61 ç
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Hunt 20 - 0.50 - 1.35
Hurt 30 - 0.75 - 1.23
Kill 490 14.60 11.35 1.45 1.26
Killer 28 0.88 0.65 2.00 1.04
Lethal 55 3.98 1.14 1.22 1.15
Mystery 30 2.21 0.62 1.20 1.20
Raging 64 0.44 1.57 1.00 1.08
Rampage 14 - 0.35 - 1.00
Stalk 1 - 0.02 - 1.00
Strike 57 0.44 1.39 1.00 1.11
Track 121 0.88 2.96 2.00 1.28
Victim 404 16.37 9.12 1.59 1.52
Plague 2,649 64.60% 62.19% 4.12 6.16
Asymptomatic 25 - 0.62 - 1.12
Cure 190 2.21 4.60 1.40 1.45
Disease 1,620 39.82 38.01 2.57 2.52
Epidemic 882 19.03 20.84 1.53 1.80
Infection 1,170 16.37 28.15 2.46 2.38
Infectious 310 5.31 7.40 2.08 1.43
Morbidity 5 0.44 0.10 2.00 1.00
Mortality 63 1.77 1.47 1.00 1.08
Mutate 34 - 0.84 - 2.18
62 ç
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Patient Zero 8 - 0.20 - 1.13
Plague 56 1.77 1.29 1.75 1.31
Sick 335 4.42 8.07 2.60 1.61
Symptom 610 10.18 14.58 1.52 1.90
Symptomatic 48 - 1.19 - 1.42
Transmission 211 3.10 5.07 1.29 1.52
Transmit 182 2.56 4.37 1.17 1.24
Viral 150 3.54 3.53 1.38 1.28
Virulence 37 0.88 0.87 1.00 1.11
Virus 1,956 29.65 46.93 1.84 2.58
War 1,311 17.70% 31.58% 1.93 2.18
Battle 188 3.54 4.47 1.00 1.17
Casualty 25 - 0.62 - 1.08
Combat 208 1.77 5.07 1.25 1.21
Conflict 43 - 1.07 - 1.09
Conquer 3 - 0.07 - 1.00
Defeat 53 0.44 1.29 2.00 1.19
Defend 46 0.44 1.12 1.00 1.22
Detain 21 - 0.52 - 1.57
Enemy 24 - 0.60 - 1.13
Fight 751 8.41 18.19 1.42 1.77
Fighter 7 - 0.17 - 1.00
63 ç
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Harbor 10 0.44 0.22 1.00 1.22
Ravage 95 0.44 2.34 1.00 1.04
Sacrifice 17 - 0.42 - 1.06
Security 267 3.10 6.46 1.43 1.31
Tackle 108 - 2.68 - 1.14
Terrorism 14 0.88 0.30 3.50 1.08
Terrorist 20 2.21 0.37 1.80 1.27
Triumph 6 0.44 0.12 1.00 1.00
Vanquish 4 - 0.10 - 1.25
Victory 9 - 0.22 - 1.00
War 97 1.77 2.31 1.25 1.47
“Othering” 1,279 23.01% 30.48% 2.35 3.27
African 397 3.10 9.69 1.57 1.55
Alien 7 - 0.17 - 1.43
Contain 366 5.31 8.80 1.58 1.59
Control 549 7.52 12.22 1.59 1.42
Distant 11 - 0.27 - 1.00
Exotic 8 0.44 0.17 2.00 1.00
Foreign 215 3.54 5.14 2.00 1.40
Isolate 461 5.75 11.13 2.31 1.76
Quarantine 355 1.77 8.72 1.00 2.39
Surveillance 129 5.31 2.91 1.08 1.83
64 ç
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Globalization 1,823 23.01% 44.00% 4.77 5.06
Airplane 22 0.88 0.50 1.00 1.15
Airport 471 3.98 11.48 1.89 2.09
Border 353 9.73 8.22 2.50 2.02
Bus 25 0.88 0.57 3.00 1.43
Entry 189 2.21 4.57 1.40 1.56
Flight 263 1.33 6.46 1.67 2.15
Global 394 1.33 9.71 1.33 1.48
Globe 33 0.44 0.80 1.00 1.03
Passenger 299 2.65 7.28 2.83 2.03
Port 135 1.77 3.25 1.25 1.79
Screen 296 5.75 7.03 2.62 2.37
Ship 63 - 1.57 - 1.87
Spread 1,051 12.83 25.39 1.90 1.82
Tourism 36 - 0.89 - 1.47
Tourist 12 0.44 0.27 1.00 1.18
Tourists 32 - 0.80 - 1.94
Trade 74 2.65 1.69 1.33 1.31
Travel 578 4.42 14.11 2.70 2.46
Visa 53 0.44 1.29 1.00 1.63
Visitor 79 0.88 1.91 1.50 1.60
World 590 6.64 14.29 1.80 1.57
65 ç
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Human Interest 1,796 38.94% 42.43% 4.33 5.07
Boy 64 0.88 1.54 1.00 2.00
Brother 49 0.44 1.19 1.00 1.65
Child 71 1.33 1.69 1.00 1.49
Children 186 3.98 4.40 3.33 1.81
Doctor 720 11.50 17.24 2.42 2.02
Emotion 26 - 0.65 - 1.35
Family 391 7.08 9.32 1.75 2.13
Father 69 0.44 1.69 3.00 1.59
Girl 70 - 1.74 - 2.01
Individual 89 - 2.21 - 1.19
Individuals 91 0.88 2.21 1.00 1.25
Man 325 3.10 7.90 1.71 1.66
Mother 102 1.33 2.46 2.00 2.11
Nurse 375 3.10 9.14 4.71 2.15
Nurses 370 4.42 8.94 3.60 1.69
Patient 1,156 23.45 27.40 2.77 2.76
Physician 119 1.33 2.88 1.33 1.34
Sister 71 0.44 1.74 3.00 1.53
Woman 158 5.31 3.63 1.42 1.92
Economic Consequences 908 11.06% 21.94% 2.08 3.32
Bought 12 - 0.30 - 1.17
66 ç
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Budget 59 0.44 1.44 1.00 1.48
Business 77 0.44 1.89 1.00 1.37
Businesses 18 - 0.45 - 1.11
Buy 40 0.88 0.94 1.00 1.26
Commerce 10 - 0.25 - 1.00
Commercial 38 - 0.94 - 1.24
Cost 168 0.88 4.12 1.00 1.42
Dollar 241 4.42 5.74 1.10 1.61
Donation 139 1.77 3.35 2.50 1.83
Economic 147 0.88 3.60 1.00 1.76
Economy 127 1.33 3.08 1.00 1.56
Employment 24 - 0.60 - 1.21
Euro 16 - 0.40 - 1.44
Finance 62 0.40 1.52 1.00 1.38
Financial 93 - 2.31 - 1.24
Fiscal 8 - 0.20 - 1.38
Fund 218 1.33 5.34 1.00 1.57
Industry 55 0.88 1.32 1.00 1.25
Investment 55 - 1.37 - 1.42
Market 115 0.88 2.81 1.00 1.73
Monetary 7 0.44 0.15 1.00 1.67
Money 165 1.77 4.00 1.25 1.39
67 ç
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Pay 99 1.33 2.39 1.67 1.24
Payment 10 0.44 0.22 1.00 1.22
Price 57 - 1.42 - 1.44
Retail 9 - 0.22 - 1.44
Attribution of 406 5.31% 9.79% 1.50 1.49 Responsibility Accountability 5 - 0.12 - 1.00
Accountable 4 - 0.10 - 1.00
Blame 80 0.44 1.96 1.00 1.15
Chaos 23 - 0.57 - 1.17
Chaotic 18 - 0.45 - 1.17
Complacency 27 0.44 0.65 1.00 1.15
Corruption 17 0.44 0.40 1.00 2.31
Delay 77 0.88 1.86 1.50 1.21
Fault 15 - 0.37 - 1.07
Guilt 4 - 0.10 - 1.50
Guilty 4 - 0.10 - 1.00
Inaction - - - - -
Inattention 1 - 0.02 - 1.00
Incompetent 20 - 0.50 - 1.15
Inept - - - - -
Ineptitude 2 - 0.05 - 1.00
Liable - - - - -
68 ç
% of Articles Mean Total No. Coding Frames 2000 2014 2000 2014 of Articles
Overconfidence 1 - 0.02 - 1.00
Passive 4 0.44 0.07 1.00 1.33
Procrastination - - - - -
Responsibilities 19 0.44 0.45 1.00 1.17
Responsibility 66 0.88 1.59 1.50 1.20
Responsible 77 1.77 1.81 1.00 1.07
Scepticism 2 - 0.05 - 1.50
Secrecy 2 - 0.05 - 1.00
Secret 17 0.44 0.40 1.00 1.25
Secretive 1 - 0.05 - 1.00
Secretly 4 0.88 0.05 1.00 1.50
Shortcoming 10 - 0.25 1.00 1.10
Skepticism 16 - 0.40 - 1.06
69