Abstract
The content analysis of reporting styles enables a rough characterization of the journalistic content with regard to the news format (news stories, commentaries, feature journalism, interviews) as well as an evaluation of the journalistic style in terms of content and language. This latter question of how content is presented encompasses many research traditions and refers, for example, to the objectivity norm, horse race coverage, storytelling or news softening. The present chapter provides a brief overview of news formats and content-related or stylistic journalistic reporting styles and discusses possible further research questions and designs as well as the contribution of automated content analysis in this field.
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1 Introduction
Journalistic reporting styles refer above all to how journalistic content is presented. On the one hand, reporting styles are the subject of practical textbooks which contain instructions for future journalists on how to apply certain reporting styles in practice (for Germany, e.g., Mast 2018; Ruß-Mohl 2016). On the other hand, reporting styles are the subject of scientific studies—the present chapter is based on this area.
From the perspective of democratic theory, the motivation to explore reporting styles is strongly normative. Since the media have the task of providing citizens with information, any deviation from factual or neutral reporting is usually seen as a potential threat to well-informed citizens and thus to democracy. Based on this way of interpretation, trends such as news softening or horse race/game framing coverage—as a result of economic constraints and the associated increasing orientation towards the audience (van Aelst et al. 2017; see also Haim 2019)—are increasingly being observed. Furthermore, it is feared that the growing importance of social media for journalism (Newman 2020) will reinforce these trends (e.g., Lischka 2021; Steiner 2016; Welbers and Opgenhaffen 2019), resulting in an even stronger audience orientation and adaptation to the so-called “social media logic” (van Dijck and Poell 2013). More generally, digital environments create completely new technological conditions, which also affect reporting styles. This includes, inter alia, more visualization, but also more live reporting (Huxford 2007) and the integration of more multimedia and interactive elements (Haim 2019).
2 Main Constructs
“Reporting styles” as a research object is multifaceted and can be assigned to different research areas—for example, research on tabloidization or research on objectivity in journalism. The most important fields of research are outlined in more detail in this chapter. When discussing research on reporting styles, a distinction is made first between 1) formal reporting styles and 2) content-related or stylistic reporting styles (by using certain linguistic means or highlighting certain aspects).
2.1 Formal Reporting Styles
The identification of the formal reporting style, that is, the form of news presentation or rather the journalistic genre, is one of the more common categories within codebooks for the study of news journalism. Separating news stories and commentaries is useful, for example, for research conducted on the norm of separating news and opinion (Schönbach 1977). There are several reporting styles to be distinguished:
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News story. A news story is the “standard format” (Weischenberg and Birkner 2008, p. 3277) in news journalism. The news story focuses only on the most important facts and presents them in order of importance. This form is called “inverted pyramid” (Pöttker 2005, p. 51; Weischenberg and Birkner 2008, p. 3278) and has its origins in nineteenth century American journalism (Pöttker 2005, p. 52). This way of news writing makes it easy to shorten the news story from the end (e.g., when taking over agency material).
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Commentary. A commentary is a “genre of journalism that provides interpretations and opinions on current events, rather than factual reporting” (Djerf-Pierre 2008, p. 566). While news stories primarily have an informative function, commentaries play an important role in the formation of public opinion (Djerf-Pierre 2008, p. 567). Apart from the classic “commentary”, the journalist’s opinion can also be found in similar news formats such as editorials or columns (Mast 2018). However, the occurrence of comments and the separation of news and comments vary between countries (Djerf-Pierre 2008, p. 567): While US journalists apply a more neutral style, journalists in southern Europe follow a more advocacy tradition and mix commentaries more with factual news coverage.
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Feature journalism. Feature journalism is a journalistic format that differs from the classic news format in that it does not use the inverted pyramid, but is rather structured chronologically (Steensen 2009). Furthermore, it often contains subjective descriptions and reflections and, as it often portrays people, is rather personal and emotional (Steensen 2009). Therefore, feature journalism is a mixture between opinion-based and objective news formats.
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Interview. The interview is a journalistic format consisting of questions (interviewer, journalist) and answers (interviewee, most often public officials such as politicians or experts) (Clayman 2008). The first printed interview appeared in 1859 in New York Tribune (Schudson 1995, pp. 73–74). While interviews were initially criticized as “artificial” and “intrusive” (Clayman 2008; Schudson 1994), they have become very important today. With the help of increasingly direct and aggressive questions, journalists also manage to stop the interviewees from using the format for mere self-representation (Clayman 2008; Schudson 1994).
Codebooks on news journalism generally distinguish between these four news formats (e.g., Kösters 2020; see also Magin 2006 with some additional news formats). Other codebooks distinguish between factual and opinionated news formats (e.g., Seethaler 2015). This distinction has become more difficult, however, as factual and opinionated formats have increasingly blurred (Schäfer-Hock 2018)—not only in private television and tabloid media, but also in the quality press, where background reporting and commentary often merge (Ruß-Mohl 2016, p. 68) (see also the trend towards more “interpretive journalism”, Salgado and Strömbäck 2012).
2.2 Content-Related or Stylistic Reporting Styles
Apart from the distinction of journalistic news formats, there are several reporting styles that deal with specific ways of how news is covered. This chapter will take up some of the more common concepts and briefly outline them.
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Objectivity. Objectivity is a journalistic goal (Cunningham 2003) which is both difficult to achieve and difficult to measure (Neuberger 2017; Ruß-Mohl 2016). However, it is an important aspect of journalistic professionalism and contains criteria such as neutrality or the negation of journalistic subjectivity, the fair representation of opposed opinions, but also telling the truth, providing all relevant information and being transparent (Bentele 1988; Donsbach and Klett 1993; Hackett 2008; Ruß-Mohl 2016). Many studies in this field of research, often in the context of news performance, analyze how neutral/impartial or subjective/partisan journalists cover specific issues, thereby referring to the concept of impartiality (Schönhagen 1998).
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Horse race coverage/game framing. Horse race coverage or game framing refers to political reporting that uses sports metaphors and sees politics as a race (of ideas, candidates) rather than focusing on factual content (Brettschneider 2008, p. 2137). This reporting style is a specific feature of election campaign reporting. Journalists focus on candidates instead of topics, as well as on polls and often over-interpret the smallest changes in popularity ratings and try to forecast the results (Brettschneider 2008; Patterson 2005). While the horse race reporting style is often criticized for trivializing election campaigns, it is also argued that it helps to increase public interest (Broh 1980, p. 515). Studies show that horse race reporting is particularly common for American election campaigns (Brettschneider 1996; Farnsworth and Lichter 2003).
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Storytelling. Storytelling describes a reporting style in which news is enriched with narrative elements to make it more interesting, meaningful and attractive for the audience (Boesman and Costera Meijer 2018, p. 997; Früh 2014, p. 93). While some journalists consider storytelling to be the “opposite of good journalism”, others rather see it as a “toolkit” to “present the facts in a good way” (Boesman and Costera Meijer 2018, pp. 1001–1002). Storytelling is also an important factor in online journalism (e.g. long-form journalism with many multimedia elements) (Jacobson et al. 2016; Meadows 2003).
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News softening. The news softening, or tabloidization, describes the adaption of tabloid standards, particularly by elite or so-called “quality” media (Esser 1999; Lefkowitz 2018; Magin 2019). It is often seen as a result of increased competitive and economic pressure and the struggle for public attention (Magin 2019; Skovsgaard 2014). However, the concept of news softening is rather a conglomerate of several concepts (for an overview see Otto et al. 2017; Reinemann et al. 2012) and therefore describes several reporting styles which are typical for tabloid media. Reinemann et al. (2012) summarize them in three sub-dimensions. The first sub-dimension refers to the topic of a news item—soft (entertainment, crime etc.) vs. hard (mainly politics) news—, and the other two sub-dimensions refer to specific reporting styles: The focus dimension means the accentuation of certain aspects within an article, for example, the focus on the individual (soft news) vs. the societal relevance or the difference between episodic framing (soft news; focus on the event itself) vs. thematic framing (focus on the thematic context). The style dimension is concerned with verbal or also (audio)visual stylistic elements. The concrete indicators for news softening in this sub-dimension vary across different studies. However, emotionalization plays a particularly important role in most of them (Reinemann et al. 2012). This includes the reporting on or visual presentation of emotions (e.g., showing crying or laughing people), but also affective wording (see also sentiment analyses, next chapter). The latter is achieved through certain linguistic elements, such as emotionalising metaphors, a short-term sentence structure, dramatizing or exaggerating adjectives etc. Another important feature is the appearance of the journalists' points of view (personal reporting; Reinemann et al. 2012; cf. objectivity norm, described further up). Apart from this, some studies also regard colloquial language or a loose language as a characteristic for softened news (e.g., Leidenberger 2015; Steiner 2016) or also use a narrative presentation (e.g., Donsbach and Büttner 2005) or the emphasis on conflicts (e.g., Donsbach and Büttner 2005; Leidenberger 2015) as indicators of softened news. Since the debate initially refers to the adaption of tabloid news standards, analyses therefore traditionally focus on newspapers (Esser 1999; Lefkowitz 2018; Magin 2019). However, research has extended to other types of media such as television (e.g., Donsbach and Büttner 2005; Grabe et al. 2001; Vettehen et al. 2008), online media outlets (Gran 2015; Karlsson 2016) and even social media (Lischka and Werning 2017; Steiner 2016) or cross-media (Reinemann et al. 2016).
3 New Research Designs and Combination of Methods
So far, the outlined concepts and indicators are usually measured using manual content analyses (e.g., Donsbach and Büttner 2005; Magin 2019; Seethaler 2015). However, like in other research areas, first steps towards automated analyses are taken. Boumans and Trilling (2016) give an overview of different approaches, ranging from strongly inductive (unsupervised machine-learning) to strongly deductive (dictionary-based methods) orientations. For each approach, they present examples from journalism research, also including reporting styles.
One of these examples is sentiment analysis. This analytical approach belongs to the field of computational linguistics and “aims at identifying and classifying subjective language” (van Atteveldt et al. 2008, p. 78). While most research in this field is based on a fixed list of words (dictionary-based approach) (Boumans and Trilling 2016; van Atteveldt et al. 2008), machine-learning approaches additionally help to analyze the context in which specific words appear (van Atteveldt et al. 2008). With regard to a similar research question, Welbers and Opgenhaffen (2019) also choose a computer-based approach. They use a lexicon for subjective adjectives and a lexicon for emoticons to investigate to which extent subjective language appears within status messages, headlines and leads of journalistic Facebook posts. Correspondingly, in her study on the tabloidization of German and Austrian elite newspapers, Magin (2019) examines the occurrence of emotional terms. She bases her study on a list (Berlin Affective word List Reloaded: Võ et al. 2009), the terms of which have previously been examined by 200 people with regard to their valence and strength of arousal. However, computer-based analyses of reporting styles are not limited to the identification of individual subjective terms. On the basis of machine-learning, those analyses can identify more complex structures and thus, for example, investigate framing (e.g., Burscher et al. 2014).
Research on reporting styles also benefits from combining findings from content analyses with other methods. Mixed-methods designs can, for example, help to identify journalists' motives or strategies for using specific reporting styles or to determine the effects on the audience more precisely. For example, Glogger (2019) uses an online survey to examine the extent to which the role expectations of journalists can affect the use of the soft news style In another study, Lischka (2021) analyzes reporting styles used within journalistic news posts on Facebook, based on qualitative interviews and a quantitative survey with social media editors from Finland and Switzerland. Furthermore, Grabe et al. (2000) use an experiment to investigate the effect that tabloid reporting style has on, for example, the memory of the recipients.
4 Research Desiderata
Due to increasing commercialisation and competitive pressure, audience orientation seems more important than ever (Haim 2019). For this reason, some authors fear that news media are increasingly focusing on how news is presented (reporting styles) instead of the content of news, which could be harmful to democracy (Blumler and Gurevitch 1995; Sparks 2000). Social media is particularly criticized for changing journalistic practices. However, it is still unclear to what extent news media adapt to the social media logic (van Dijck and Poell 2013) and neglect professional standards for the sake of attention-oriented reporting styles. With regard to news softening, first studies (e.g., Lischka 2021; Steiner 2016; Welbers and Opgenhaffen 2019) indicate that there is no complete departure from professional standards. However, future research should pay more attention to how news media adapt to communicative developments such as the increased importance of social media for news consumption. In addition, more studies should investigate the extent to which criticism of certain reporting styles is justified and what positive effects these reporting styles can have (e.g., Bernhard 2012; Frey 2014).
Furthermore, outlining the different concepts and indicators of reporting styles in this article has shown that journalistic reporting styles are very complex and thus not easy to measure. If researchers want to apply automated methods (e.g., machine-learning) to enlarge their data set, they may first need a sufficient amount of (manually coded) training data (e.g., see Burscher et al. 2014 on the importance of the amount of training material for the performance of the classifiers). For this reason, it is not only important that researchers share their data (see Dienlin et al. 2021 for the call for open science), but also that they use the same instruments (e.g., see Reinemann et al. 2012, p. 225 on the problem of “conceptual fuzziness” with respect to news softening) so that their data can be used by other researchers.
Relevant Variables in DOCA—Database of Variables for Content Analysis
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Formal reporting style: https://doi.org/10.34778/2r
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Impartiality: https://doi.org/10.34778/2s
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Soft news/tabloidization: https://doi.org/10.34778/2t
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Klein, M. (2023). Content Analysis in the Research on Reporting Styles. In: Oehmer-Pedrazzi, F., Kessler, S.H., Humprecht, E., Sommer, K., Castro, L. (eds) Standardisierte Inhaltsanalyse in der Kommunikationswissenschaft – Standardized Content Analysis in Communication Research. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-36179-2_6
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