Media frames in German news media during key events in the refugee crisis 2015
An exploratory research of German public broadcast TV news using hierarchical cluster analysis
Master Thesis in Communication Science University of Amsterdam
Political Communication
Anne Rupp 10864342
annerupp1991@gmail.com Supervisor: Sanne Kruikemeier
Abstract
Scholars agree that frames have an impact on the perceptions that individuals in a society hold and can influence public opinion on an issue such as immigration. Triggered by the events of the refugee crisis in 2015 this study looks at the media frames in German news media before and after key events during the crisis in order to detect shifts in frames. To identify issue-specific frames a new framing approach introduced by Matthes & Kohring (2008) is tested and applied to a new context since it promises to improve validity and reliability. Based on their original codebook, 127 (N=127) news shows in a time period of two weeks in August and September 2015 were coded. Frames were detected with an exploratory framing approach using hierarchical cluster analysis. Results showed that the negative bias found in prior research on immigration could not uphold, which brings other contextual factors into the picture that are likely to account for the media’s behavior. Factors like the discourse in the political sphere or the media’s behavior in times of crisis should be included in future research models in order to test their relationship in this specific case.
Media frames in German news media during key events in the refugee crisis 2015 Empirical research has investigated the topic of migration in the media in various ways, both internationally (Entman & Rojecki, 2000; Browne, 2005; Blinder & Allen, 2013) and for Germany specifically (Ruhrmann, Sommer & Uhlemann, 2006; Ruhrmann & Demren, 2000; Hömberg & Schlemmer, 1995; Ruhrmann & Sommer, 2005 & 2010).
Across Germany, several scholars have looked at how media treats migrants in a wide range of news outlets and over several periods of time. The results have shown that immigrants – whether it regards asylum applicants (Homberg & Schlemmer, 1995) or migrants living in Germany (Ruhrmann & Sommer, 2005; Ruhrmann, Sommer & Uhlemann, 2006) – are mostly portrayed in a negative light, often combined with reports about crime and under the dominant news factors conflict and negativity.
From what is known about the effects of frames this can have crucial implications for public opinion on the issue. Researchers of media effects within or beyond the well-established research field of framing and framing effects agree, that mass media are a major source of information for people and ultimately play a role in forming attitudes about certain issues, including immigration (Boomgaarden & Vliegenthart; 2009; Scheufele, 2004; Lecheler & de Vreese, 2012; Geschke, Sassenberg, Ruhrmann & Sommer, 2010). It is therefore important to constantly assess the media environment, especially regarding the sensible topic of racial minority groups, in order to determine the kind of thinking that is encouraged by certain media frames.
Evaluating news behavior in this matter is especially important since there seems to be a constant negative bias in the news about migrants, further influenced by societal and political circumstances such as the high numbers of asylum applicants in the 1990s (Hömberg &
Schlemmer, 1995) or terror attacks worldwide (Ross, 2003; Just, Kern & Norris, 2003). The terror attacks of 9/11, for example, have shifted the focus of media reportage and brought back conflicts between different social and ethnic groups (Just, Kern & Norris, 2003; Hafez & Richter, 2007).
Considering the influence of key events on news topics, recent developments give rise to a reevaluation since the events of 2015 triggered a heated political debate, that could once again lead to a shift in news narratives.
As of December 2015, more than 911,000 refugees, the majority of them Syrians fleeing the war, have arrived in Europe, making 2015, as a report of the UNHCR (Spindler, 2016) puts it, ‘The Year of Europe’s Refugee Crisis’. The events of 2015 have prompted extensive media coverage and dominated the headlines in Europe and across the world. People’s responses to the events unfolding in 2015 reached from sympathy and euphoria in Munich (Connolly, 2015) to skepticism, harsh critique and even outright hatred towards the foreign ‘unknown’. Apparently, the conflict in the Middle East has reached Europe and Germany with two faces. Apart from terror attackers, we are suddenly also confronted with the people fleeing from those attackers and bringing with them the stories of a war that seemed far away just a few month ago. Through the lens of Germany, the country that took in more refugees than any other country (“2015: Mehr Asylanträge in Deutschland als jemals zuvor”, 2015), we can observe competing
discourses between Xenophobia and ‘Willkommenskultur’ (welcome culture) in the presence of an unknown future (Holmes & Castaneda, 2015).
Examining the media’s behavior becomes especially important for Germany, if the integration of such high refugee numbers in German society is to be successful. Based on the assumption that the events of the refugee crisis in 2015 constitute an influential key event, this
research will look at the topics and frames present in German news media. In order to detect the specific topics emerging during the refugee crisis a newly introduced framing approach by Matthes & Kohring will be tested in the analysis since it promises to improve validity and reliability when coding issue-specific frames compared to older framing approaches. Key events during a set time period were selected in order to look at the dynamics of frames before and after those events.
RQ: Which topics and frames are used in German news media during a predefined time period in the refugee crisis and how do these topics and frames relate to specific key events?
Theory Section The Framing Approach
A frame is defined as a “central organizing idea or story line that provides meaning to an unfolding strip of events, weaving a connection among them. The frame suggests what the controversy is about, the essence of the issue” (Gamson & Modigliani, 1987, p. 143). Based on the assumption that the way a topic is presented or characterized in a news story can have an effect on how it is perceived by its audience, framing research looks at the interaction between journalist, other communicators and recipients through media content (Scheufele 2004 & 2006; Scheufele & Tweksbury, 2007).
Due to its long tradition and increasing prominence in the communication research field, scholars today can draw from a broad and diverse set of literature that contributed to the field in various ways (Gamson & Modigliani, 1987; Gitlin, 1980; Brosius & Eps, 1995; Entman 1993; Just, Kern & Norris, 2003; Scheufele, 2003, 2006 & 2007; Matthes & Kohring, 2008; de Vreese, 2012). While some have looked at the effects of existing frames considering cognitive patterns (de Vreese, 2005; Scheufele, 2003 & 2007), others have focused at the frame building process
taking into account structural factors of journalism and media such as the interaction between journalists and elites or the role of journalism in a specific media system (Gans, 1979; Tuchman, 1978; Shoemaker & Resse, 1996; Scheufele, 2003; Bennett, 1990; Brüggemann & Weßler, 2009).
And even though the results of this complex field are rich and varied, most of the research agrees that mass media and the salient frames in them have a significant influence on the perceptions that individuals in society hold (Boomgaarden & Vliegenthart, 2009; Scheufele, 2004; Lecheler & de Vreese, 2012; Geschke et. al., 2010, Vliegenthart, Schuck, Boomgaarden & De Vreese, 2008). As Scheufele (2003) suggests, it is even a “necessary tool to reduce the complexity of an issue” and making it “accessible to lay audiences because they play to existing cognitive schemas.”
Following this, looking at existing media frames through content analysis is an essential step in framing research, since it helps to understand possible effects on recipients. Analyzing existing frames helps to understand patterns or discourses of certain issues, based on the
assumption that the way of presenting an issue can have an influence on how it is understood by audiences (Scheufele & Tewksbury, 2007). In relation to the refugee crisis, this insight explains the societal relevance of this study. The outcome is expected to have implications on public opinion around immigration, which in return can define how Germany as a country deals with the challenge of the highest number of refugees since the Second World War (“2015: Mehr Asylanträge in Deutschland als jemals zuvor”, 2015).
Furthermore, framing is a suitable approach when dealing with dynamics and changes in news coverage (Scheufele, 2006). Since this study is based on the assumption that the refugee crisis 2015 constitutes an influential key event that could cause a shift in news coverage, the
framing approach is the logical choice when looking at the dynamics of news narratives before and after key events. In order to substantiate this assumption, the influence of key events on frames and the event of the refugee crisis as such a key event, shall receive further attention in the following chapter.
Frames and Key Events: The Refugee Crisis ‘arriving’ in Germany
According to several scholars (Brosius & Eps, 1995; Kepplinger & Habermeier, 1995; Scheufele, 2006), key events play an important role in shaping media frames. Frames need to change according to real life events in order to fit to current observation of the situation (Scheufele, 2006). Normally, these changes happen slowly and gradually (Scheufele, 2006), however some suggest that not every event has the same impact. Scholars like Kepplinger & Habermeier (1995) or Molotch & Lester (1974) distinguish between standard events and key events. Standard events around a specific issue happen frequently and within the standard procedures of reporting, whereas key events occur less frequently. They have to contain a certain sensation or immediacy and often have the power to trigger news waves or cause changes in frames (Brosius & Eps, 1995; Kepplinger & Habermeier, 1995, Scheufele, 2003).
Following this, the present study argues that the refugee crisis fulfils the criteria of a key event, although first an exact time period for the analysis needs to be defined. The refugee crisis as a whole developed over a longer period of time and would offer several influential events with varying importance depending on the perspective (“Migrant crisis: Nine key moments from the last year”, 2015). In order to look at shifts in frames and sharpen the focus of the research, the time period of the analysis needs to be narrowed down to specific dates that can serve as point of reference marking some kind of change.
have the potential to represent such a reference point.
On the 31st of August, Angela Merkel made the momentous decision to let refugees from Hungary pass the border to Germany regardless of the standards of the Dublin Agreement followed by the two consecutive events on the 3rd and 5th of September as described in table 1.
Table 1: Timeline of Events in September
31. August, Berlin Merkel holds press conference where she says the famous phrase “Wir schaffen das” and decides to not reject trains arriving from Hungary 3. September 2015 Hungary stops the trains. Thousands of refugees are stuck at the train
station and decide to start walking to the Austrian border determined to 5. September. Merkel speaks to Hungarian president Viktor Orbán and Austrian
chancellor Werner Faymann. Merkel and Faymann decide to let the refugees pass the border as a reaction to the chaotic situation in
A consequential moment from a German perspective. Even though steady number of refugees were already entering Europe before, the number of refugees at that point in time reached an unforeseen high putting excessive demands on European authorities regarding the coordination and administration of the ‘floods’ of refugees. In return, it prompted extensive media coverage and marked a changing point in the European and German reality with thousands of refugees arriving in Munich the 5th of September.
Germany and other countries have always been handling altering numbers of immigration, but the unusual number of refugees and apparent unexpectedness of the immigration flow ultimately gave the event the name of a ‘crisis’ (Coombs, 2007 & 2015), imposing an administrational task on Germany and Europe.
As indicated in table 1, authorities were clearly at risk to lose control over the situation and fast decisions were required. When political actors are under pressure to make
fast decisions about a situation, media organizations are an important instrument to get their message across.
In former studies (e.g. Scheufele, 2006, Just, Kern & Norris, 2003) key events where found to shape news selection in a one-sided way, leading to one dominant frame with low frame competition, a result that is especially likely in times of crisis. According to
Brüggemann & Weßler (2009) or Bennett (1990), this is most likely a result of elite
consensus and high cultural resonance of the dominant frame. This indicates that the role of the media under certain circumstances is highly dependent on contextual factors. In order to tell more about these contextual factors and the media’s ‘usual’ behavior, prior research on the issue of immigration needs to be considered.
The Media and Ethnic Minorities
A fair amount of research has dealt with immigration and racial minority in media and most of the studies that look at the content of different news outlets observe a negative portrayal of immigrants by presenting them as a problematic or criminal group. This was found in
countries around the world (Entman & Rojecki, 2000: Browne, 2005; Blinder & Allen, 2015) and specifically for Germany (Ruhrmann, Sommer & Uhlemann, 2006; Ruhrmann & Demren, 2000; Hömberg & Schlemmer, 1994; Ruhrmann & Sommer, 2005 & 2010). Within this negative bias, immigrants are portrayed as passive objects that are judged or victimized (Ruhrmann & Sommer, 2005; Ruhrmann, Sommer & Uhlemann, 2006). There are also
neutralizing reports about integrated migrants, but often these positive reports remain the lower proportion and are used as an exceptional or untypical subcategory of the overall negative stereotype (Hömberg & Schlemmer, 1994). In terms of news values, the migration topic is mostly stressed by the news factors negativity (Ruhrmann, 2002) as well as conflict, aggression,
damage and demonstration (Brosius & Esser, 1995).
In conclusion, former research on immigration detected few positive frames used when covering immigrants or refugees in Germany, which is generally seen as dangerous since it reinforces existing fears and stereotypes and often doesn’t display reality (Geißler & Menges, 2009). Considering the high number of refugees that came to Germany in 2015, a negative bias in media could have harmful consequences for society.
However, since the mentioned studies were conducted under diverse circumstances and during different time periods, the question remains whether this negative bias is an effect that can always be expected in the media coverage of ethnic minorities or if other contextual factors are likely to influence the framing process.
Studies dealing with the migration topic also link the news coverage to key events in real life discourse (Brosius and Eps, 1995, Norris, Kern & Just, 2003; Hafez & Richter, 2007). For example, the observed shift in frames after the terror attacks of 9/11 again displayed a negative bias towards migrants, but showed a shift towards Muslim immigrants as a possible terrorist threat (Just, Kern & Norris, 2003; Hafez & Richter, 2007).
Related to this, a more recent study by Abadi, d’Haenens, Roe & Koeman’s (2016) focuses on the political debate around Muslim immigrants in Germany and comes to a more differentiated conclusion when looking at the discourse in German newspapers between 2009 and 2014. Compared to other findings, the treatment of migrants in this time period in Germany was mainly led by a ‘pragmatism frame’ suggesting a more neutral attitude towards the topic. But most importantly their results confirm that topics from real life discourse (in their case Sarrazin’s publication ‘Deutschland schafft sich ab’) can trigger political debate, suggesting a dependency of contextual factors.
Also Zambonini (2009) somehow relativizes the negative bias towards migrants by relating the media’s portrayal of immigrants in Germany to the political debate over time, offering a prospect of hope for the future driven by a general societal change regarding Germany’s image as an ‘immigration country’ and paradigm shifts in Germany’s immigration policies. His paper suggests that the political debate as a context factor can play an important role in shaping media frames, a factor that was already subject to many research dealing with the role of media in framing processes (Lester & Molotch, 1975, Bennett, 1990; Brüggemann & Weßler, 2009).
Scholars dealing with frame building processes suggest that news is inherently
subjective and to a certain degree biased, although it does not happen intentionally (Scheufele & Tewksbury, 2007; Dijk, 1991, Entman, 2007). Instead, various structural, organizational and professional features were found to be influential in shaping news frames, from the journalist’s personal values or work ethics to external influences such as the organizational structure of the news room or a country’s media and political system (Schoemaker & Reese, 1996, Scheufele, 2003).
Following this, it would be impetuous to assume that media is generally negatively biased towards immigrants, even though this was often the case in prior research. Instead, the topic of immigration was found to be dependent from real life factors such as key events. It is therefore likely to assume that the nature of the key event and the contextual factors
surrounding it, will ultimately play a role in shaping the frame topics around immigration. However, in order to control for these contextual factors, an extensive research design (e.g. measuring the discourse in the political sphere) would be required that would exceed the scope of this research project. Their influence should be acknowledged in order to explain
different outcomes, but the present research cannot make assumption about the concrete influence of context factors on the resulting frames. Instead, the research design in this study has to remain exploratory, with the aim to identify the topics and frames emerging during the refugee crisis openly. Furthermore it will focus on the dynamics of frames surrounding the identified key events, which led to the following research question:
RQ: Which topics and frames are used during a predefined time period in the refugee crisis and how do these topics and frames relate to specific key events?
Method
One aim of the study, as discussed in the theory, is to identify the frames and frame dynamics around the refugee crisis present in German news media. On the one hand, this serves a societal relevance by giving insight into media frames of a highly relevant topic, on the other hand, the study contributes to the research field on immigration by reevaluating prior results. In order to do so, the study will use a relatively new framing method introduced by Matthes & Kohring (2008), which fits the purpose of this analysis. However, the approach has not been applied to a broad range of topics yet. Testing their approach in a new context and for a different media type will be a second aim of this study, contributing to the academic research field of framing by pursuing and testing a framing approach that was found to improve reliability and validity. For the analysis, a quantitative content analysis was conducted using hierarchical cluster analysis.
The Matthes & Kohring Approach
In order to answer the above research question, an in-depth approach is required that is able to detect issue specific frames in a time-sensible manner. One method that promises to fulfil these demands is a new method introduced by Matthes & Kohring (2008). The method was
proposed in order to enhance reliability and validity during the coding procedure and is a useful approach for the purpose of this study, since it is designed to detect issue-specific frames that are still collected in a quantitative manner, rather than being derived from a merely interpretive qualitative approach.
Based on Entman’s (1993) widely accepted definition, suggesting that to frame is to “select some aspects of a perceived reality and make them more salient in a communicating context, in such way as to promote a particular problem definition, causal interpretation, moral evaluation and/or treatment recommendation“ (Entman, 1993, S. 52), Matthes & Kohring propose to split up the frame in its microelements instead of directly coding the whole frame. As a response to the growing concerns of scholars in the field about the reliability and validity in content analysis of media frames (as cited in Matthes & Kohring, 2008: ‘Gamson, 1989, p. 159; Gandy, 2001, pp. 360–361; Hertog & McLeod, 2001, p. 153; Miller, 1997, p. 376;
Scheufele, 1999, p. 103; Tankard, 2001, p. 104’), their new framing approach uses a method of hierarchical cluster analysis, that is supposed to overcome these problems by coding variables for single frame elements, and in a second step, clustering them together in order to reveal frame patterns, making the coding process more objective and reliable compared to purely qualitative, hermeneutic approaches or completely computer-assisted quantitative approaches. Frames are “empirically determined” instead of “subjectively defined”, but are still able to go beyond solely generic frames (Semetko & Valkenburg, 2000) that have the disadvantage of being static and not sensible to the dynamic of frames.
Sample
For the analysis, 127 (N=127) news units related to the refugee crisis were coded in the main news shows of Germany’s two public broadcasters: tagesschau and ZDF heute.
The decision for only one type of media was made to ensure a better comparability, with television still being the most important medium for political information among Germans (VPRT-Medienanalyse, 2015). Furthermore, the coding of TV shows will add to the novelty of the study by applying the Matthes & Kohring (2008) approach to a different form of media ‘text’. Among TV news, the public broadcasters have an important position in Germany, holding almost half of the overall shares in the TV news landscape (VPRT-Medienanalyse, 2015). In order to get a more complete picture of the TV news landscape, including private channels in the sample as well would have been useful, however accessing data from past programs is restricted for those TV channels, whereas the news shows from the public broadcasters can be accessed in their online archive, making it possible to freely select time periods in the past for the analysis.
Since this leaves us with the public broadcast channels only, it has to be mentioned that the German public broadcasters, ARD and ZDF, are special in the sense that they are tax
financed and supposed to act according to a governmental contract (Die Medienanstalten, 2013) that obliges them to broadly inform the German citizens about international, European, national and regional events in an objective and neutral manner, considering all important areas of life. Following the above criteria, it can be presumed that their organizational structure provides the right preconditions for an objective and independent reporting. Due to their organizational nature, it can be assumed that factors like economic pressure are reduced to a certain degree compared to private media outlets. Since the economic pressure can be expected to be smaller, public media outlets will be less dependent from sensational or populist content, however they could be more dependent from state actors (Brüggemann & Weßler, 2009).
retrieved from their respective online archive (“ARD Mediathek - Startseite - Videos und Audios zum Abruf”, n.d.; “ZDF Mediathek – Top-Themen”, n.d.) between the 24th of August and the 7th of September. This time period was chosen starting seven days prior to the first key event, on the 31st of August, and ends on the 7th of September, thereby including the
consecutive events on the 3rd and 5th of September (see Table 1). The time before the 31st of August represents the period before the first key event.
Data and Coding
The codebook for the analysis was based on the original codebook used by Matthes & Kohring (2008), including variables for the following elements: problem definition, causal interpretation (or attribution), moral evaluation, and treatment recommendation. In order to adapt the codebook to the topic of the refugee crisis, multiple pre-tests of coding were run to define the themes and actors that were included in the codebook. The codebook used in this study was first used in 1997, and proved to meet standards of criteria in various context, which is why this study was confident to achieve the required standards of reliability. In order to test for the inter-coder reliability of the adjusted codebook, a second coder coded 8% of the overall sample, using Krippendorff’s alpha (α) as a measure (Hayes & Krippendorff, 2007). In some cases, the reliability was weaker due to the wide range of codes possible for these variables. These reliability measures could however be improved after refining the codes to more narrow categories (see Appendix B).
Frame Elements, Variables and Measures
The frame element problem definition includes variables on type of event, theme and actor. Following Matthes & Kohring (2008), three themes were coded together with a single main actor and the location of the event. For the location variable, four possible locations could
be coded, which were later grouped together to variables describing for example transit zones in border regions or certain travel routes (e.g. Greece, Serbia, Macedonia, Hungary = Balkan route).
Even though the coded themes serve to get insight into the specific problems discussed during the crisis, we also included a general code that defined the crisis in general as the ‘problem’, since often the demand or proposed solution took a more prominent place in a frame, while the problem definition was pre-defined through the crisis situation. The variable for the element treatment recommendation will therefore get more weight in this research than it is the case in the example used by Matthes & Kohring (2008). Corresponding to the different types of demand formulated in the crisis, three possible types (Stop refugees from entering (1), Support refugees (2), reduce/control number of refugees (3)) were included that could then be combined with an area of demand and a call for action or the demand to stop the action. Along with the demand variable in the treatment recommendation element, author and addressee of demand were included as well as a judgement variable on two levels: First, the judgement of the refugee crisis (situation is under control vs. situation is not under control) could be coded either positively or negatively and second, the refugees as a group could be evaluated
positively or negatively. In the case of balanced coding, of course also a neutral judgement could be concluded.
For the frame moral evaluation risk and benefit variables were identified together with the variable that describes the responsible actor for respective risk or benefit, which makes up the frame element causal attribution. In addition to the actor variable for causal attribution, I followed the example of David, Atun, Fille & Monterola (2011), who already applied the Matthes & Kohring (2008) approach in a different context and added a variable for responsible
factors, since benefits or risks in this case could also be associated with certain policies. Furthermore, a variable for nationality was included for every actor in the codebook.
Like in the example codebook adopted from Matthes & Kohring (2008), exactly the same codes of the ‘main actors’ were used for the variable ‘responsible actors’ just as the same codes of the ‘main themes’ were used for ‘responsible factors’ and ‘area of demand’. In a next step the variables were recoded according to their occurrence in the units of analysis, which lead for example to other groups of actors attributed to benefits or risks than the main actors. Originally 49 themes, ranging from coordination measures for arriving refugees such as refugee camps or reception centers to integration measures for refugees, and 47 actors were included in the codebook (See Appendix A). In a next step, all the variables were further refined by grouping them together in meaningful ways using simple crosstab analysis. If for example ‘government’ in the main actor variable frequently occurred together with the nationality ‘Germany’ a variable for ‘Government Germany’ was created.
In this step, I already excluded the variables that didn’t occur at all or only in very small numbers (less than 5%). Table 2 shows an overview of all the variables that were finally used for the hierarchical cluster analysis including the means (M) and standard deviations (SD). Before conducting the hierarchical cluster analysis all variables were recoded into binary variables.
Table 1 Variables and Codes for Cluster Analysis
Frame Element Variables Description M (SD)
Problem Definition Topic: Policy Changes
Topic: Coordination Measures Topic: Crisis General
Topic: Arrival of refugees Topic: Travel Routes Topic: Public Opinion Main Actor: Angela Merkel Main Actor: Government Germany Main Actor: CSU Bayern
Main Actor: Opposition Main Actor: Public Sector Main Actor: The public Main Actor: Refugees Main Actor: EU
Main Actor: Government Eastern EU Main Actor: Government Other EU Location: Germany Regions Location: Germany
Location: EU (Summits) Location: Mediterranean Sea Location: Balkan Route
Location: Balkan Route + Austria Location: Hungary Germany Austria Location: Eastern EU
Location: Austria
Reception Centers, Refugee Camps, Transit Zones, Registration, etc.
The Green Party, The Left Party, SPD
Government institutions, education sector, health insurances, police/military
EU parliament or EU commission
Hungary, Poland, Slovakia, Slovenia, Macedonia France, Denmark, Sweden, Spain, UK, Italy
0.26 (0.44) 0.17 (0.38) 0.25 (0.43) 0.11 (0.31) 0.15 (0.35) 0.05 (0.22) 0.06 (0.24) 0.11 (0.31) 0.08 (0.26) 0.02 (0.15) 0.04 (0.19) 0.03 (0.17) 0.42 (0.5) 0.05 (0.21) 0.03 (0.18) 0.08 (0.26) 0.05 (0.22) 0.38 (0.48) 0.06 (0.23) 0.09 (0.28) 0.07 (0.25) 0.03 (0.18) 0.02 (0.13) 0.08 (0.27) 0.03 (0.18)
Moral Evaluation Benefit: Economic
Benefit: Social Cultural or Moral Ethical Benefit: administrational
Benefit: Safety Risk: economic
Risk: social cultural or moral ethical Risk: administrational Risk: safety 0.04 (0.2) 0.13 (0.33) 0.15 (0.36) 0.03 (0.18) 0.02 (0.13) 0.05 (0.22) 0.23 (0.42) 0.15 (0.37)
Risk: legal
Risk: political consent
0.03 (0.18) 0.04 (0.2)
Causal Attribution Benefit Attribution: Government Germany
Benefit Attribution: Government Austria Benefit Attribution: Public Sector Benefit Attribution: Public Support Benefit Attribution: EU Government Benefit Attribution: Favorable Policies Benefit Attribution: Unfavorable Policies Benefit Attribution: Coordination Measures Benefit Attribution: Labor Market
Risk Attribution: Government Germany Risk Attribution: Government Eastern Europe Risk Attribution: The Public
Risk Attribution: Refugees General Risk Attribution: ‘Unwelcome’ Refugees Risk Attribution: Traffickers
Risk Attribution: Favorable Policies Risk Attribution: Unfavorable Policies Risk Attribution: Coordination Measures Risk Attribution: Number of Refugees Risk Attribution: violent or criminal actions Risk Attribution: International Agreements
Donations, volunteer work, support through demonstrations
Social Benefits, Financing, Integration Measures, open borders, etc. deportation, closed borders, entry requirements, max. limit of refugees,
Refugees from crisis regions, mainly Syria
e.g. refugees with ‘no right to asyl’ (e.g. from Balkan States)
Dublin Agreement, Schengen Agreement, Asylum Law
0.04 (0.2) 0.13 (0.33) 0.15 (0.36) 0.13 (0.34) 0.01 (0.10) 0.11 (0.31) 0.03 (0.17) 0.05 (0.21) 0.02 (0.13) 0.07 (0.26) 0.09 (0.21) 0.04 (0.21) 0.01 (0.07) 0.02 (0.15) 0.05 (0.22) 0.05 (0.23) 0.04 (0.2) 0.16 (0.37) 0.07 (0.3) 0.10 (0.3) 0.02 (0.15) Treatment Recommendation
Demand: Favorable Policies to support refugees Demand: Stop fav. policies to stop ref. from entering Demand: Adhere to Int. Agreements to control crisis Demand: unfav. policies to stop refugees from entering Demand: unfav. policies to reduce number of refugees Demand: Coordination Measures to reduce n of ref. Demand: Coordination Measures to support refugees Demand: stop Coordination Measures to support ref. Demand: Financing to support refugees / solve crisis Demand: Quota to solve crisis
Demand: stop Quota (no to Quota) Demand: Public Support
Author Demand: Angela Merkel
refusal to register in Hungary
0.05 (0.22) 0.03 (0.17) 0.03 (0.18) 0.03 (0.17) 0.09 (0.29) 0.06 (0.23) 0.17 (0.38) 0.02 (0.15) 0.11 (0.31) 0.08 (0.27) 0.01 (0.11) 0.04 (0.19) 0.09 (0.3)
Author Demand: Government Germany Author Demand: Government Eastern Europe Author Demand: Other EU countries
Author Demand: UK Author Demand: CSU
Author Demand: regional political Actors Author Demand: Opposition
Author Demand: Organizations Citizen Organizations, professional organizations (e.g. UNHCR)
Author Demand: EU Author Demand: Public Author Demand: Refugees
Addressee Demand: Government Eastern Europe Addressee Demand: Government Germany
Addressee Demand: Government Italy/Greece/Turkey Addressee Demand: Public
Addressee Demand: refugees (general) Addressee Demand: refugees ‘unwelcome’ Addressee Demand: EU
Addressee Demand: countries in EU
Addressee Demand: regional Political Actors
0.14 (0.35) 0.05 (0.22) 0.03 (0.18) 0.03 (0.18) 0.03 (0.18) 0.06 (0.24) 0.04 (0.21) 0.04 (0.21) 0.02 (0.16) 0.01 (0.13) 0.03 (0.18) 0.03 (0.17) 0.05 (0.22) 0.08 (0.27) 0.15 (0.36) 0.03 (0.17) 0.01 (0.13) 0.06 (0.23) 0.06 (0.23) 0.07 (0.25)
Judgement Judgement: slightly critical to crisis situation
Judgement: critical to crisis situation Judgement: very critical to crisis situation Judgement: slightly positive to crisis situation Judgement: positive to crisis situation
Judgement: very positive to crisis situation Judgement: slightly critical to refugees Judgement: critical to refugees
Judgement: very critical to refugees Judgement: positive to refugees Judgement: very positive to refugees
0.04 (0.21) 0.25 (0.44) 0.16 (0.37) 0.07 (0.26) 0.13 (0.34) 0.04 (0.19) 0.01 (0.10) 0.02 (0.13) 0.01 (0.11) 0.05 (0.23) 0.01 (0.07)
Results
A hierarchical cluster analysis (Ward method) was carried out for each of the two periods. As indicated by Matthes & Kohring (2008), the Ward method is considered a good technique for identifying suitable cluster solutions (as cited in Matthes & Kohring, 2008: Breckenridge, 2000, p. 281; for binary variables, see Hands & Everitt, 1987, p. 242). The number of clusters was
determined by computing a dendrogram using the squared Euclidean distance dissimilarity measure together with the values of the Duda– Hart Je(2)/Je(1) stopping rule and the pseudo-T- squared values, both indicating the number of clusters that should be generated. A large Je(2)/Je(1) index value and a small pseudo-T-squared value indicate distinct clustering (Rabe- Hesketh & Everitt, 2007).
In order to look at the differences in clustering before and after the first key event (31st of August) a
hierarchical cluster analysis was conducted separately in August and September to see what differences would be visible in the respective clusters.
Frames emerging between the 24th and 31st of August
The dendrogramm and values of pseudo T-squared for the news shows in August (n=55) already indicated that the clusters were not sufficiently distinct from another and results could be unclear. This assumption was confirmed in the next step when looking at the generated clusters. Combining the variables showed that clusters were too heterogenic to draw meaningful conclusions and clear frames didn’t emerge.
Frames emerging between the 1st of September and the 7th of September
In the first week of September the topic not only received higher attention (n=55 vs. n=72) in the media, the cluster analysis also showed clear frames emerging. This already supports the first hypothesis that a shift in frames can be observed after the first key event on the 31st of August, with clear frames emerging after the first key event compared to the inconclusive frames in August.
A hierarchical cluster analysis was conducted with 5 distinct clusters each representing one frame. At first, the pseudo-T-values showed distinct enough values for the first three clusters, however the dendrogramm also suggested a possible five-cluster solutions. After testing both possibilities the five-cluster solution proved to be the better choice in terms of clarity and
interpretability, since the three-cluster solution would have resulted in a third cluster that was too heterogeneous. In the tables below the variables for each frame elements are presented as
clustered in their respective frame.
As Matthes & Kohring (2008) already note, the mean values of binary variables are “problematic in statistical terms” however it is considered suitable for this approach. The higher the mean, the more important the variable. Generally, values below 0.05 (5%) were not reported, however there can be exceptions to this rule, for example, if a value occurs exclusively in one cluster. In such a case even low values could still be important for the interpretation of the frame.
Table 3 shows the mean values (M) of all variables loading on the first cluster. This first frame deals with the arrival of refugees in Germany or Austria. 86% of the topics deal with the arrival of refugees and the news event is either taking place in Germany, Austria or on the border region to Austria. Characteristic of this frame is the high percentage of benefits mentioned. 43% of the news shows with this frame mention an administrational benefit, followed by 21% social and cultural or moral and ethical benefits and 14% safety benefits.
Administrational risks are also present (21%), but the responsible actors are controversial. On the one side is the German government with favorable policies and on the other side the eastern European governments with failed coordination measures.
Table 3: Frame Elements and Variables in Cluster 1: Safety and Order in Western Europe
Frame Elements Variables M
n=14 Topic/Theme Actor Location Coordination Measures Crisis General Arrival of refugees Refugees Germany
Balkan Route + Austria (Border Region) Germany + Austria (Border Region) Austria 0.07 0.07 0.86 0.93 0.21 0.07 0.21 0.07 Benefit Social & Cultural or Moral & Ethical
Administrational Safety
0.21 0.43
0.14 Benefit Attribution German Government
Public Support Favorable Policies Coordination Measures 0.14 0.50 0.07 0.29
Risk Administrational (chaos) 0.21
Risk Attribution Germany Government
Eastern European Governments Favorable Policies
Failed Coordination Measures Number of Refugees 0.07 0.07 0.07 0.07 0.07 Demand/Solution Author of demand Addressee of demand
Adhere to International Agreements (control Crisis) Coordination Measures to support refugees
Quota to solve crisis Public Support
Government Germany Austria
regional Political Actors Public Sector
Organizations Public
Government Eastern European States regional political actors
0.07 0.21 0.14 0.07 0.07 0.07 0.14 0.07 0.07 0.07 0.21 0.21
Judgement slightly positive to crisis situation positive to crisis situation very positive to crisis situation positive to refugees
0.07
0.36 0.50
0.07
On the contrary, the benefits are clearly attributed to the German government (14%) and even more so to the German public (50%) accounting for an apparently well working system (28% for coordination measures).
Demands are coming from Germany (7%) and Austria (7%) and are mostly directed to the authorities in Eastern Europe being critical about their policies towards refugees (demand for coordination measures, 21%) and their handling of the crisis (adhere to international agreements 7%).
Other demands are related to a fair redistribution of refugees in Europe as a solution to the crisis and the demand for support among the public (7%). Besides the national governments of Germany and Austria, authors of demands involve to a smaller percentage regional political actors (14%), the public sector (7%) and professional organizations (7%).
It should be noted that in this case it was not always possible to clearly attribute one type of demand to one single actor, which is why in this case it is also likely that the demand for coordination measures is partly voiced from e.g. professional organizations and directed to regional political actors (21%) referring to coordination measures within Germany after the arrival of refugees. A prominent aspect of this frame is that the handling of the crisis is judged very positively, with 50% of the news shows showing a very positive judgement of the crisis situation. The situation is clearly portrayed as ‘under control’ and also refugees themselves are portrayed in a rather positive light (7%). Germany and Austria seem to be portrayed as a place of safety and support.
In table 4 the elements of the second cluster seem to describe the counter frame to the safety frame in the first cluster.
The most important topics are distributed in coordination measures (30%), travel routes (22%) and public opinion (17%), with the refugees as the main actor in 70% of the articles. Taking place on the main refugee travel routes like the Balkan route (17%) or the Mediterranean Sea Route (26%) and other eastern countries of the EU (43%).
Table 4: Frame Elements and Variables in Cluster 2: Chaos in East Europe
Frame Elements Variables M
n=23 Topic Main Actor Location Policy Changes Coordination Measures Crisis General Arrival of refugees Travel Routes Public Opinion Refugees EU Meditarenean Sea Balkan Route
Balkan Route + Austria
Eastern Europe (Hungary, Macedonia, Serbia)
0.09 0.30 0.09 0.13 0.22 0.17 0.70 0.09 0.26 0.17 0.09 0.43 Benefit Administrational 0.09
Benefit Attribution National Government Austria Public Support Coordination Measures 0.04 0.04 0.04 Risk administrational safety 0.43 0.39
Risk Attribution National Government Germany National Government Eastern Europe Unfavorable Policies Coordination Measures Number of Refugees 0.09 0.35 0.09 0.48 0.09 Demand/Solution Author of demand Addressee of demand Judgement
Favorable Policies to support refugees
stop favorable policies to stop refugees from entering adhere to International Agreements to control crisis Coordination Measures to reduce number of refugees Coordination Measures to support refugees
stop Coordination Measures to support refugees stop Quota (no to Quota)
Government EastEU EU Refugees Government EastEU Government Germany Gov Italy/Greece/Turkey critical to crisis situation very critical to crisis situation neutral towards refugees
0.09 0.04 0.04 0.09 0.39 0.09 0.04 0.13 0.09 0.35 0.22 0.09 0.17 0.22 0.09 0.78
Contrastive to the first frame the benefits mentioned in this frame are very little (9%) and solely attributed to the Austrian government (4%) or support from the public (4%).
On the other hand, the risks clearly stand out. 43% of this frame mentions
administrational risks and 39% of the time safety risks are present, which are mostly attributed to the eastern European governments (35%) and their unfavorable policies (9%) or failed
coordination measures (48%). Partly, but significantly lower, also the German government (9%) is mentioned as a responsible actor or the quite neutral attribution of numbers of refugees (9%) as a responsible factor.
In the treatment recommendation element the contradictory network of different authors and demands shows the obvious disagreement of state actors across Europe regarding the
solution of the crisis at this point. Whereas the eastern European countries (9%) demand a stop of favorable policies towards refugees (4%) and say no to the demand of a fair redistribution of refugees (4%) the EU (35%) and the refugees themselves (22%), who get a strong voice in this frame, demand to control the situation (coordination measures to reduce number of refugees, 39%) or support the refugees with favorable policies (9%).
One unique demand present in this frame is the demand to stop coordination measures in order to support refugees (4%). This demand refers to the refusal of the refugees to get registered in Hungary and demanding to be let through to Germany and other northern European States to apply for asylum. Just as the situation in the first frame was judged highly positive, this frame is extremely critical towards the crisis situation clearly implying that the situation is not under control (78%). The frame is neutral in its judgement towards refugees. Furthermore, the refugees play a remarkably active role in this frame being the main actor in 70% of the cases and voicing their own demands. Alongside the ‘safe-place’ Germany, Hungary and other eastern European states apparently represent chaos and viciousness.
The third frame in table 5 deals with the handling of the crisis in Germany (82%
Germany in location variable) mainly addressing policy changes (0.67%) and the crisis situation in general (25%). Here, mainly political actors within the government (33%) and from the public sector (17%) are involved.
Table 5: Frame Elements and Variables in Cluster 3: Refugees Welcome?
Frame Elements Variables M
(n=12) Topic/Theme Actor Location Policy Changes Coordination Measures Crisis General Angela Merkel Government Germany Public Sector Refugees Government Other EU Germany 0.67 0.08 0.25 0.08 0.33 0.17 0.33 0.08 0.83 Benefit Economic
Social & Cultural or Moral & Ethical
0.17 0.17
Benefit Attribution Public Support Labor Market 0.17 0.17 Demands/Solutions Author of demand Addressee of demand
Favorable policies to support refugees
Unfavorable policies to reduce number of refugees Coordination Measures to support refugees
Quota to solve crisis Angela Merkel
Government Germany regional political actors Government Germany Public Sector
refugees (general) refugees unwelcome Member countries of EU regional political actors
0.17 0.08 0.17 0.08 0.08 0.83 0.08 0.08 0.08 0.17 0.08 0.08 0.17
Judgement critical to crisis situation
slightly positive to crisis situation positive to crisis situation
positive to refugees
0.08
0.17 0.17
Angela Merkel as a single actor appears in 8% of the cases as well as the EU. In 33% of the cases refugees are the main actor. The emphasis in this frame is on the benefits, when e.g. mentioning refugees as a possible economic benefit (17%) on the labor market.
Furthermore, the social and moral benefits through public support are often present (17%), whereas no risks are mentioned at all. In the treatment recommendation frame it becomes visible that the demands for favorable policies (17%) are accompanied by demands to reduce the number of refugees (8%), even though the favorable demands clearly overweigh. This divide is further explained in the addressee variable, were a division between welcome and ‘unwelcome’ refugees becomes visible (17% welcome refugees vs. 8% unwelcome refugees). The unfavorable policies seem to be directed to a special group of ‘unwelcome’ refugees.
Considering the unity of authors of demands, where only governmental actors appear, it can be assumed that this frame mainly displays a governmental frame showing Angela Merkel and her cabinet’s position on the situation, which is mainly positive and favorable, but excluding special groups of refugees that are considered unwelcome. Refugees from this groups address mostly refugees from Balkan states that are supposed to be classified as safe countries of origin in order to make deportation of these refugees easier.
In table 6 the least clear frame among the five clusters is presented, including a lot of different and partly contradictory variables. So are here for example favorable policies attributed to risks as well as benefits. Proposed solutions are opposed to each other with demands to stricter policies towards refugees versus demands to support refugees.
Unlike the four other frames, this example is definitely the cluster with the least clear results, which however could mean that this frame displays the political debate around the issue. One aspect that speaks for this explanation is the high presence of more conservative and
Table 6: Frame Elements and Variables in Cluster 4: Political Debate
Frame Elements Variables M
n=12 Topic Actor Location Policy Changes Coordination Measures Crisis General Arrival of refugees Government Germany CSU Bayern Refugees EU Germany
Hungary Germany Austria (border region) Eastern Europe (Hungary, Macedonia, Serbia)
0.17 0.17 0.58 0.08 0.17 0.17 0.42 0.08 0.50 0.08 0.08 Benefit Social Cultural or Moral Ethical
administrational Safety
0.17 0.33 0.17 Benefit Attribution National Government Germany
National Government Austria EU Government Favorable Policies 0.67 0.08 0.08 0.67 Risk economic
social cultural or moral ethical administrational
0.08 0.17 0.08 Risk Attribution National Government Germany
The public Favorable Policies Unfavorable Policies 0.17 0.08 0.17 0.08 Demand Author Demand Addressee of demand
Stop favorable policies to stop refugees from entering Adhere to International Agreements (control crisis) Unfavorable policies to reduce number of refugees Coordination Measures to support refugees
stop Quota (no to Quota) Government Germany Government Eastern Europe CSU
regional Political Actors Opposition
Government Germany Public Sector refugees (general) refugees ‘unwelcome’ 0.08 0.08 0.08 0.25 0.08 0.08 0.08 0.25 0.08 0.08 0.17 0.08 0.08 0.08 Judgement Balanced towards crisis situation
positive towards refugees
0.68 0.17
Opponents of Merkel’s favorable policies such as the conservative governing-party CSU or Eastern European state actors voice their opinions in this frame but are also opposed vice versa by the German government or voices from the opposition. Regarding the judgement, the frame is rather neutral and even quite positive towards refugees (17%) suggesting a positive position of the media despite the negative demands present in the frame.
Lastly, in the fifth cluster in table 7 the crisis is addressed by various European and German actors, with Angela Merkel (33%) apparently leading the conversation.
The central element of this frame is the demand for a mutual European agreement in the refugee question (45%), with Germany and other Western European countries demanding a fair redistribution of the refugees across all EU member countries. Usual opponent and main
addressee of the demands are again the governments of Eastern Europe (27%) who don’t seem to play along with the call for European solidarity. The risks present therefore regard risks in the political sphere such as political disagreement (18%), administrational (27%) and even moral or ethical (9%) risks suggesting an expected moral obligation from Europe. Additionally, a
controversy about international agreements such as the Dublin Agreement or the Schengen Agreement becomes visible (Risk through violation of international agreements: 27%, demand to adhere to International agreements: 18%).
The variables in this frame show the clear divide among Europe regarding the solutions of the crisis. The call for solidarity from important actors in the EU doesn’t seem to be fruitful. As a result, international agreements and the European Union itself are at risk.
Table 7: Frame Elements and Variables in Cluster 5: European Solidarity
Frame Elements Variables M (SD)
(n=11) Topic Theme Policy Changes
Crisis General
0.27 0.73
Actor
Location
Angela Merkel CSU Bayern EU (Organisation)
Government from Eastern European States Governments from other EU countries EU-Summits (e.g. Brussels or Luxembourg) Hungary Germany Austria (Border Region)
0.36 0.18 0.18 0.18 0.27 0.64 0.09 Risk social & cultural or moral & ethical
administrational (chaos) political disagreement
0.09 0.27 0.18 Risk Attribution National Government Germany
Failed Coordination Measures
Violation of International Agreements/Laws
0.36 0.09 0.27 Demands/Solutions Author Demand Addressee Demand
Adhere to International Agreements (control crisis) Call for Coordination Measures to support refugees Call for fair redistribution (solve crisis)
Angela Merkel
Government Germany
Government Eastern European States Other EU countries
UK
EU (Organisation)
Government Eastern European State Government Germany
Public
Member countries of the European Union
0.18 0.36 0.45 0.09 0.18 0.09 0.09 0.27 0.18 0.27 0.09 0.09 0.27 Judgement Negative towards crisis situation
Very negative towards crisis situation Positive towards refugees
0.45 0.27 0.09
Frame Dynamics and Key Events
Figure 1 shows the frequencies of the presented five frames over time with the date as independent and the five generated clusters as dependent variable.
It can be observed that the ‘safety’ frame from Cluster 1 as well as the ‘welcome’ frame (Cluster 3) and the ‘political debate’ frame (Cluster 4) all grew strongest after the arrival of the refugees in Munich on the 5th of September, whereas the ‘Chaos’ frame was mostly present in the time before, where refugees were still held in Hungary. It reached a peak on the 4th of September after refugees decided to walk to the Austrian border because they weren’t able to enter the trains
in Budapest. The ‘solidarity’ frame was present during the whole period representing the solution as proposed by the European Union and powerful member countries such as Germany.
Figure 1. Number of frames between the 1st and 7th of September, 2016
Following the timeline of the events in September the figure above illustrates nicely the dynamics of frames during this time period that seemed to follow a clear line along the key events with a clear shift in frames after the 31st of August and even a second shift on the 5th of September. The Media and Ethnic Minorities
What could be surprising about these results is that we can find indeed a quite positive framing of refugees in the emerged frames, with favorable policies and humanistic attitudes towards refugees and the situation as a whole. The demand to support refugees is present in all of the five frames and in three out of the five frames the positive treatment of refugees clearly overweighs. The crisis itself naturally imposes a risk, but most of the time it is not the refugees who are made responsible for its negative implications. Instead the coverage in September shifts its focus towards opponents within the European Union, namely the Eastern European States like Hungary or Slovakia who clearly support unfavorable policies towards refugees. There is a clear divide between frames of safety and shelter in Germany versus chaos and ill-treatment in
Hungary and other Eastern European States, which is seen critically in German media. Also within the European Union the proposed solutions to handle the crisis imply a favorable and humane treatment of refugees. The results even suggest a moral obligation element in the frames ‘European Solidarity’ and ‘Safety and Order’, a results that seems surprising regarding prior results on immigration coverage. In the second frame that addresses the chaotic situation in Eastern European countries, refugees even get to play an active part, formulating demands and voicing their discomfort with the situation.
Furthermore the public plays an important role in the ‘welcome’ frame by being responsible for a great share of the benefits for refugees through e.g. donations or volunteer work (‘public support’).
This is not to say however, that there is no negativity at all towards refugees in the ‘German’ frames. In the third frame (‘Refugees Welcome?’) the demand to support refugees clearly stands out, but along with it a differentiation between welcome and unwelcome refugees is present. Alongside the demand to support the ‘welcome’ refugees, right after the arrival of thousands in Germany, those refugees now also seem to serve as the argumentation for the unfavorable treatment of ‘unwelcome’ refugees. The necessity to make a selection is formulated, where apparently one group has to step back in order to support the other group, which could however also be called a ‘pragmatic’ frame by justifying the unfavorable treatment towards unwelcome refugees with the favorable treatment of welcome refugees. This demand mainly affects those coming from Balkan States like Albania or Kosovo, which are supposed to be declared as safe third states as a responding measure to reduce the number of refugees.
Discussion and Limitations
The frames emerging between the 31st of August and 7th of September showed that shifts in frames occurred before and after key events. The analyzed dynamics of frames furthermore indicated that the frames followed a clear dynamic along the identified key events. This result supports the previous assumption about the refugee crisis representing a key event that can cause a shift in frames. The media’s behavior in the period between the 31st of August and 7th of September furthermore strengthens the previously
formulated presumption that different contextual factors around the event could have
implications for the media’s behavior beyond the topic of immigration. So could for example the crisis character of the event lead to certain patterns of media behavior that could ultimately account for the surprisingly positive results towards refugees that deviate from previous media coverage on immigrants and refugees.
Research has found that mass media seem to have a tendency to rely on frames from politicians and favor sources with political and economic power, a mechanism that is
particularly likely in situation of crisis or international conflict (Tuchman, 1978; Gans, 1979; Hallin, 1984; Bennett, 1990; Schoemaker & Reese, 1996, Brüggemann & Weßler, 2009). One model that was mentioned earlier comes from Brüggemann & Weßler (2009) and builds up on the prominent indexing hypothesis from Bennett (1990) according to which media only
displays the perspectives that are present in the political sphere. Brüggemann & Weßler (2009) describe the relationship between elites and media as one of mutual dependency and assume that the outcome of media frames depends on a range of factors which can ultimately lead to different forms of reporting varying from conflict to conflict or country to country. Previous research they refer to has shown that in times of crisis the media is likely to follow a one-sided
news selection adopting the prominent frames imposed by powerful political actors. The dominance of certain frames can be further influenced by a high cultural resonance in society (Brüggemann & Weßler, 2009).
Taking all this together, these factors could very well play into the context of the refugee crisis coverage, considering the outcome of this research.
The media coverage during the analyzed time period seems to reflect some observations from politics and society that could indicate a dependency of those factors. Angela Merkel’s clear and determined position on the refugee crisis produced worldwide responses and the thousands of volunteers welcoming refugees at the Central Station in Munich made the world look at Germany as the country that showed a friendly face in the crisis (Conolly, 2015). This could partly explain the positive tendencies of media coverage, possibly imposed by the strong lead of Angela Merkel, who arguably made fast and determined decisions in a situation of crisis. Furthermore the strong public support could suggest an acceptance of the positive frame in society.
Concluding, it is very likely to assume that context factors again played an important role in the media’s treatment of immigrants while still following recognizable patterns of media behavior. The results of this study still show tendencies of media bias, but in this case it seemingly shifted towards other state actors that were held responsible for the risks
imposed by the crisis still conforming to the common news value negativity (Galtung & Ruge, 1965).
Unfortunately, due to the relatively small sample and limited research frame of this study it is not possible to make concrete assumptions about these context factors, which is why this research suggests to further pursue the topic with an extensive research approach
that is suitable to measure media frames as well as context factors. Since the time period analyzed in this research was relatively small it can for example not be assumed that the media wouldn’t also return to its usual negative treatment of immigrants or that critical voices wouldn’t emerge after a certain amount of time, e.g. when the media has returned to a state of routine.
After all it could very well be that the crisis character added a dimension to this event that skewed the media’s behavior. In order to draw conclusions about the mentioned
contextual factors a cross-country approach over a longer period of time would be necessary in order to control for different societal and political circumstances. Nevertheless, the
exploratory approach of this study lead to informative results that raised interesting questions for further research. Further research has to tell whether the positive treatment of refugees was a short whiled exception or whether Germany has really changed regarding its immigration approach and its image as an ‘immigration country’.
Regarding the tested research approach of Matthes & Kohring (2008) it should be noted that the quality of the frames and their reliability ultimately depend on the way the approach is applied to a new context, since adjustments are necessary in every case. The research process and pre-tests in this case have shown that frame elements are not equally important in every context, so was for example the treatment recommendation variable much more important in this case than it was for the biotechnology topic researched by Matthes & Kohring (2008).
Furthermore the topic of the refugee crisis seemed to have more dimensions that required additions to the codebook which resulted in a higher number of variables for the cluster
analysis. As a result, not all the variables in a resulting cluster could be linked perfectly to each other since there was a wider variety of variables that occurred together. This could also be
due to the fact that TV news were analyzed instead of written text, since news segments with spoken text could be less definite than a newspaper article.
Following this, it also depends on the interpretative work of the researcher to make the analysis meaningful by transforming the frame elements to a new context, which means that there will be some degree of bias from the researcher involved. Still, the emerged frames were not predictable prior to the analysis due to the coding process of single frame elements, which rightfully supports Matthes & Kohring’s arguments about reliability and validity in the framing research.
The cluster results in this study have shown that meaningful frames can emerge even with a larger set of variables and a relatively small sample. Also applying the approach to TV news instead of newspaper articles was found to be convertible with the provided codebook. Taken together, the cluster analysis proposed by Matthes & Kohring (2008) was found to be a useful approach that is applicable to various topics and should be further pursued by other research that is interested in measuring issue-specific frames in a reliable and objective manner.
References
ARD Mediathek - Startseite - Videos und Audios zum Abruf. (n.d.). Retrieved from: http://www.ardmediathek.de/tv (June 21, 2016)
Bennett, W. L. (1990). Toward a Theory of Press-State Relations in the United States. Communication Journal of Communication, 40(2), 103-127. doi:10.1111/j.1460- 2466.1990.tb02265.x
Blinder, S., & Allen, W. L. (2015). Constructing immigrants: Portrayals of migrant groups in British national newspapers, 2010-2012. International Migration Review, 50(1), 3–40. doi:10.1111/imre.12206
Boomgaarden, H., & Vliegenthart, R. (2009). How news content influences anti-immigration attitudes: Germany, 1993-2005. European Journal of Political Research, 48(4), 516-542. http://dx.doi.org/10.1111/j.1475-6765.2009.01831.x
Brosius, H., & Eps, P. (1995). Prototyping through Key Events: News Selection in the Case of Violence against Aliens and Asylum Seekers in Germany. European Journal of
Communication, 10(3), 391-412. doi:10.1177/0267323195010003005
Brosius, H., & Esser, F. (1995). Eskalation durch Berichterstattung? Massenmedien und fremdenfeindliche Gewalt. Opladen: Westdeutscher Verlag
Browne, D. (2005). Ethnic minorities, electronic media and the public sphere. Cresskill, N.J.: Hampton Press.
Brüggemann, M., & Weßler, H. (2009). Medien im Krieg. Das Verhältnis von Medien und Politik im Zeitalter transnationaler Konfliktkommunikation. Politik in Der
Connolly, Kate (2015). Germany greets refugees with help and kindness at Munich central station. Retrieved from: http://www.theguardian.com/world/2015/sep/03/germany- refugees-munich-central-station (March 26, 2016)
Coombs, W. T. (2007). Protecting organization reputations during a crisis: The development and application of situational crisis communication theory. Corporate Reputation Review, 10(3), 163–176.
Coombs, W. T. (2015). Ongoing crisis communication: Planning, managing, and responding. California: Sage Publications.
David, C. C., Atun, J. M., Fille, E., & Monterola, C. (2011). Finding Frames: Comparing Two Methods of Frame Analysis. Communication Methods and Measures, 5(4), 329-351. doi:10.1080/19312458.2011.624873
de Vreese, C. H. (2005). News framing: Theory and typology. Information Design Journal + Document Design, 13(1), 51–62. doi:10.1075/idjdd.13.1.06vre
de Vreese, C. H. (2012). New avenues for framing research. American Behavioral Scientist, 56(3), 365–375. doi:10.1177/0002764211426331
Die Medienanstalten (2013). Staatsvertrag für Rundfunk und Telemedien (Rundfunkstaatsvertrag - RStV). Berlin: Die Medienanstalten. Retrieved from: http://www.die-
Dijk, T. A. (1991). Racism and the press. London: Routledge.
Entman, R. M. (1993). Framing: toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51-58
Entman, R. (2007). Framing Bias: Media in the Distribution of Power. Journal of
Communication, 57(1), 163-173. http://dx.doi.org/10.1111/j.1460-2466.2006.00336.x Entman, R. M., & Rojecki, A. (2000). The black image in the white mind: Media and race in
Galtung, J., & Ruge, M. H. (1965). The Structure of Foreign News: The Presentation of the Congo, Cuba and Cyprus Crises in Four Norwegian Newspapers. Journal of Peace Research, 2(1), 64-90. doi:10.1177/002234336500200104
Gans, H. J. (1979). Deciding what's news: A study of CBS evening news, NBC nightly news, Newsweek, and Time. New York: Pantheon Books.
Gamson, W. A., & Modigliani, A. (1987) The Changing Culture of Affirmative Action. Research in Political Sociology (3), 137–177.
Geißler, R., & Weber-Menges, S. (2009). Media Reception and Ideas on Media Integration among Turkish, Italian and Russo-German Migrants in Germany. European and North American Perspectives Media - Migration - Integration. doi:10.14361/9783839410325- 001
Geschke, D., Sassenberg, K., Ruhrmann, G., & Sommer, D. (2010). Effects of Linguistic Abstractness in the Mass Media: How Newspaper Articles Shape Readers’ Attitudes Toward Migrants. Journal of Media Psychology Theories, Methods and Applications, 22(3), 99-104.
Gitlin, T. (1980) The Whole World is Watching. Mass Media in the Making and Unmaking of the New Left. Berkeley: University of California Press.
Hafez, K. & Richter, R. (2009). Das Islambild von ARD und ZDF. Themenstrukturen einer Negativagenda. Fachjournalist. (3),10-16.
Hayes, A. F., & Krippendorff, K. (2007). Answering the Call for a Standard Reliability Measure for Coding Data. Communication Methods and Measures, 1(1), 77-89.
doi:10.1080/19312450709336664
Hallin, D. C. (1984). The mass media and the crisis in American politics: The case of Vietnam. Michigan: Univ. Microfilms Internat.
