Keywords

1 Introduction

Research on news performance is rooted in normative ideas of the public sphere and expectations about the benefits of the news media for individuals and society (McQuail 1992). News performance is a key concept in communication science with a long tradition of research (Eisenegger et al. 2010; Ferree et al. 2002; McQuail 1992). While earlier studies mainly focused on print media, research in the last decade has increasingly focused on online content and participatory journalism (Burggraaff and Trilling 2020; Humprecht 2016; Rowe 2015). The underlying assumption is that news performance has declined in the digital age and that citizens are increasingly poorly informed (or disinformed) (van Aelst et al. 2017). Potential drivers for this development are seen in the increasing commercialization, the rise of new and alternative media, and changed habits of media use (Humprecht and Udris 2019). Against this background, scholars are interested in long-term changes in news content and increasingly apply longitudinal designs in research on news performance (Vogler et al. 2019).

Another recent trend is cross-national comparative research (de Vreese et al. 2017). However, there are still relatively few studies comparing more than two countries. Comparative designs allow for contextualizing the effects of global phenomena such as the globalization and commercialization of media markets on news performance (Humprecht and Esser 2018b). Moreover, such designs help researchers to identify country-specific drivers for changes in news performance (Humprecht and Udris 2019).

Finally, certain aspects of news performance, such as diversity, have recently been studied in new ways, e.g. in forms of diversity created by algorithmic recommenders (Möller et al. 2018). These new fields of research underline the topicality of this traditional research area, which is constantly evolving.

2 Frequent Designs

News performance has traditionally been investigated in communication studies using quantitative, manual content analysis (Ferree et al. 2002; Imhof 2010; Neuberger 2018). Those studies focus on the analysis of political reporting, often during election campaigns, on specific political issues, or routine reporting (Albæk et al. 2017; de Vreese and Boomgaarden 2012). More recent studies on news performance also apply computational approaches or combinations of manual and automated approaches; however, these approaches are still comparatively rare (Boumans and Trilling 2016; Karlsson and Sjøvaag 2016; Scherr et al. 2019). Additionally, manual content analysis is frequently combined with other methods, such as expert interviews (Sehl 2013) and surveys (Engesser 2012). Current research increasingly includes digital trace data in order to make statements about the reach of certain media content (Burggraaff and Trilling 2020).

The vast majority of studies on news performance are single-country studies. Thus, the generalization of research findings is difficult because of their varying understanding of normative ideals related to the news media and, accordingly, the nature of news performance. Thus, scholarship has called for more cross-national research on news performance that makes explicit their underlying normative foundations. A key study in this area is that of Ferree et al. (2002). The study compares the discourse on abortion regulation in the US and Germany and links the results to different images of an ideal public sphere. Comparative research on news performance often focuses on transnational developments, such as the digitalization, commercialization, and mediatization of politics (Aalberg et al. 2013; Benson and Hallin 2007; Strömbäck and Esser 2014). Furthermore, commercialization has studied across different types of news outlets. Various ownership types have been found to differ regarding their profit orientation, which has been found to be reflected in news performance (Benson et al. 2018; Humprecht and Esser 2018a).

3 Main Constructs

Empirical studies investigating news performance sometimes use the term ‘quality’ when refereeing to news performance (Schatz and Schulz 1992). However, the notion of quality is controversial because it heavily depends on cultural and political contexts. Quality can be understood differently and examined from different perspectives, namely, the perspective of consumers, media organizations, or society as a whole. McQuail (1992) argues that news performance is a more appropriate concept to investigate the ‘quality’ of media content. He links this concept to the functions of public communication and mass media in democracies rooted in normative theories of the news media. These theories refer to the value of news content for the audience in democratic decision-making. In other words, different news media functions can be accounted for and interpreted in the context of their institutional environments. Based on this understanding of news performance, research evaluates the media’s output in the light of its democratic functions.

Following this line of thought, scholars have defined key elements underlying the theoretical assumption of news performance linked to functions of democracy (Benson 2013; de Vreese et al. 2016; Humprecht 2016; Imhof 2010). In the following, frequently used constructs in studies using content analysis are discussed.

  1. 1.

    Diversity: The concept of diversity is frequently linked to the information function of the media and the idea that the news media should provide a wide range of relevant information (Christians et al. 2009). More recent research has focused on diversity in the context of algorithmic recommenders (Möller et al. 2018) and social media platforms (Steiner et al. 2019). Scholars frequently analyze the diversity of speakers (Benson and Wood 2015; Humprecht and Esser 2018a; Steiner et al. 2019), viewpoints (Baden and Springer 2014; Ho and Quinn 2009; Masini et al. 2018), and topics (Napoli and Gillis 2008; van Hoof et al. 2014). The diversity of speakers is frequently measured with actor lists, which are developed for their respective contexts (e.g. candidates in national elections, government representatives in different countries, different types of political and public actors, etc.). Viewpoint diversity is often measured by analyzing various frames or interpretations of the same issues (Baden and Springer 2015). Finally, topic diversity is measured either by using predefined topic lists or by employing topic modeling, for example LDA models (van der Meer 2016). To measure the distribution of different categories in content analysis, diversity indices are frequently used, e.g. the Shannon entropy index (Napoli and Gillis 2008).

  2. 2.

    Hard news vs. soft news: The provision of hard news has been theoretically linked to the accountability function of news media (Cushion 2012; McQuail 2010). The idea is that the news media hold political actors and institutions accountable to the public by providing in-depth and background information. Reinemann et al. (2012) suggest three dimensions for the measurement of hard news, namely focus, topic, and style. The focus dimension refers to specific aspects of events or topics, namely the societal vs. individual relevance of a covered topic as well as thematic vs. episodic framing. The topic dimension is operationalized by the political substance of the covered topics, e.g., the mentioning of authorities, societal actors, the substance of decisions, and affected groups. Finally, the style dimension refers to the way events or topics are presented, as reflected in the personalization (impersonal vs. personal reporting) and emotionalization (emotional vs. unemotional reporting) of news coverage

  3. 3.

    Analytical depth: Similar to the hard news/soft news concept, analytical depth presents the idea that news media should provide in-depth information to help citizens understand why and how political decisions are made (Benson 2011). Frequently used operationalizations include categories such as the explanation of an event’s cause or history (e.g., a thorough description of how the event occurred), a change in perspective (the provision of different perspectives, not only viewpoints), the level of justification, and analytical quality (e.g., analysis-centered reporting) (Humprecht 2016). In addition, the accountability function has often been linked to the watchdog role of news media. In content analyses, the watchdog role has been measured by coding whether a critical perspective on authorities and probing questions asked of the responsible actors are present in news content (Humprecht 2016).

  4. 4.

    Deliberation: Deliberation is a concept rooted in discursive and participatory theories of the news media (Habermas 2006; Wessler 2008). With the rise of participatory journalism and social media platforms, expectations of a democratization of public discourse have been articulated (Gerhards and Schafer 2010). Subsequently, many researchers have investigated the deliberative quality of digital platforms and comment sections (see chapter on Hate Speech/Incivility in this volume) of online news (Esau et al. 2017; Karlsson et al. 2015; Rowe 2015). Since deliberation is a complex concept, operationalizations differ tremendously. Rowe (2015), for example, used categories such as the expression of opinion, the direction of opinion, justification, sources, and narratives for the measurement of deliberation. Ziegele et al. (2018) measured the inclusiveness of discussions by coding individual commenters per article and the diversity of opinions. Further, those authors measured deliberative interactivity by counting the numbers of received civil and rational comments and shares per article. Finally, Benson et al. (2012) studied deliberation in print and online newspapers in France, Denmark, and the US and focused on the presence of interview transcripts, polls, online chats, and forums.

4 Research Desiderata

Research on news performance remains focused on print newspapers and their websites (Karlsson and Sjøvaag 2016). Therefore, empirical results are limited to a few major print brands, whereas actual offers—and usage—are much broader. This phenomenon can be partially explained by the routines and conventions of scholarship in the field of communication studies. The current literature is largely informed by the standards of research, routines, and practices established by print journalism, and thus, recent studies often apply ‘existing lenses’ to the study of news performance. Prior to the rise of online outlets and digital platforms, news was classified according to media types, such as print, TV, or radio (Mitchelstein and Boczkowski 2009). However, this practice is not suitable for the digital media landscape. Online news combines text, audio, and video, and reporting might be shaped by a thematic focus instead of technological constraints. Thus, it appears necessary to take into account different types of online platforms when studying news content to provide a more diverse picture. Only a few studies, for example, analyze differences in the news performance of media brands on their websites and on social media, e.g. Facebook (Steiner et al. 2019; Welbers and Opgenhaffen 2019). Moreover, some central aspects of news performance, including source transparency, have received comparatively little attention in previous research. In the context of digital media, source transparency has been discussed with regard to journalists’ fact-checking efforts (Graves 2013). However, only a few studies explicitly examine source transparency in the context of news performance (Lecheler and Kruikemeier 2016; Revers 2014).

In sum, the main research gaps discussed in the literature concern the absence of original approaches to the study of digital news, the need for studies that focus on content instead of technology, the need for longitudinal approaches, and an absence of large-scale comparative studies. Moreover, an evaluation of online news content against a background of normative theories can assist in gaining a better understanding of the effects of digitalization and other global phenomena on journalistic routines and news content.

Relevant Variables in DOCA—Database of Variables for Content Analysis