In this introduction, we draw together the articles in the special issue on the platformization of news, highlighting that the articles contribute by answering two central questions. First, what is the extent of contemporary journalists and news organizations’ platform dependence, and how does this vary according to geographic context, organizational resources, and other factors? Second, what is the nature of journalism’s platform dependency? Platforms’ most overt editorial influence on news publishers (e.g., dictating areas of coverage, reshaping headlines, and so on) has arguably waned in recent years – and was never straightforward to begin with. The articles in this special issue encourage us to consider how the platform/publisher relationship is now defined by more subtle, or even hidden, dependencies that are nevertheless impactful. We further argue that various forms of power are at play in the shifting, contextual and embedded configurations of dependency and autonomy in the platform/publisher relationship. The forms of power, which we can observe across the articles, and which matter for dependence/autonomy configurations, are infrastructural, cultural, and geopolitical.

To understand how journalism is made and what news is, it is helpful to center “the press” as an object of analysis and concern, a way to see the conditions under which news is made and made meaningful. For several years, many scholars and practitioners have focused on “the platform press” as a new way of understanding how journalism is made and what news is. In this essay I argue that that this “platform press” view enables three vital, generative ways to see the press: as platform labor, as a chance for normative honesty, and as an opportunity to take a long view of journalism and news.

What makes people share political news on Facebook? Prior studies have identified how different features predict audiences’ likelihood to share news on social media – the so-called shareworthiness of news. However, we still know very little about the relative contributions of these different features for predicting why people decide to share news. We extend the literature by using an experimental design that can compare the relative importance of several key features that contribute to shaping citizens’ sharing decisions: a conjoint experimental design. We use an identical layout to Facebook and a probability sample of Norwegian citizens. We find that particularly content characteristics are important, and that popularity cues and message congruence is conditional on some user characteristics such as age.

In recent decades, significant transformations in audience characteristics and the media environment have necessitated a reassessment of audience analysis. Communication scholars have increasingly recognized the value of utilizing digital traces as valuable resources to understand audience behaviors. This research presents a comprehensive review of 243 audience analyses that incorporate digital traces, covering the period from 2001 to 2022, as published in 19 prominent communication journals. Our analysis reveals a remarkable expansion in the variety of data sources and a diversification of research contexts within the field. The integration of digital traces has empowered researchers to enhance behavioral concepts and attain deeper insights into audience dynamics. By harnessing the temporal, semantic, and structural information embedded within digital traces, novel audience metrics have been developed. This review identifies noteworthy theoretical and methodological implications for future audience research, emphasizing the necessity to embrace the evolving landscape of digital media. Furthermore, it suggests avenues for further exploration and the refinement of existing methodologies. By capitalizing on the potential of digital traces, communication scholars can continue to advance our understanding of audience characteristics and behaviors in the ever-changing media ecosystem.

During the 2019 Indian general election, Indian prime minister Narendra Modi launched his #MainBhiChowkidar (I am also a watchman) campaign, which can be understood as an attempt to undermine the institutionalized watchdog or monitoring system, including journalism, in democratic India. Through the lens of positioning theory, this qualitative study examines how 89 Indian journalists responded to Modi’s populist campaign on Twitter. Findings show that the Indian journalists used self-positioning but especially other-positioning practices to discursively negotiate their position as watchdogs of Indian society. The other-positioning practices reveal that the journalists position Modi and his followers as “fake” and “failed” Chowkidar by providing evidence that the self-appointed Chowkidars are derelict in fulfilling their duties as watchmen. Thus, instead of engaging in an outright discursive struggle with Modi over the watchdog position in society, Indian journalists upheld their position by acting like watchdogs.

While fact-checking has received much attention as a tool to fight misinformation online, fact-checking efforts have yielded limited success in combating political misinformation due to partisans’ biased information processing. The efficacy of fact-checking often decreases, if not backfires, when the fact-checking messages contradict individual audiences’ political stance. To explore ways to minimize such politically biased processing of fact-checking messages, an online experiment (N = 645) examined how different source labels of fact-checking messages (human experts vs. AI vs. crowdsourcing vs. human experts-AI hybrid) influence partisans’ processing of fact-checking messages. Results showed that AI and crowdsourcing source labels significantly reduced motivated reasoning in evaluating the credibility of fact-checking messages whereas the partisan bias remained evident for the human experts and human experts-AI hybrid source labels.

Given the importance of fact-checking in reducing the spread of false information on social media, prior research has examined effective fact-checking strategies. The current study addresses this question by conducting a computational analysis of actual fact-checking tweets of three representative fact-checking organizations in the United States (Factcheck.org, PolitiFact, Snopes), replies, and retweets (N = 166,526) on Twitter made from September 29 to November 3, 2020, when the 2020 U.S. presidential election and the COVID-19 crisis co-occurred. The results show that fact-checking tweets with a greater degree of anxiety and anger generally receive more replies, but those exhibiting sadness are retweeted less. Additionally, fact-checking tweets with heightened levels of anxiety, anger, sadness, or negativity, in general, tend to elicit replies featuring a degree of anxiety, anger, sadness, or negativity, respectively. Our findings suggest that emotions can be utilized as drivers of engagement in fact-checking tweets, meaning that the emotional impetus can potentially serve as an important strategy to make fact-checking efforts more impactful in uncertain situations. However, fact-checking organizations should be aware that emotional appeals in fact-checking posts catalyze correspondingly emotional responses from their audiences, which reflects the emotional contagion process.

Understanding the impact of digital media on news inequalities is critical for democracy. The literature on incidental exposure challenges the idea that major platforms shrink information gaps, and research has turned to the identification of variables that explain how those gaps widen or persist. We use Latent Class Analysis to operationalize the metaphor of “attracting the news” and investigate incidental exposure as both an individual trait and temporal state. We link the top stories on Facebook during an election cycle with incidental exposure measures to explore news attraction, incidental exposure, and news engagement. We find some evidence incidental exposure may close information gaps, but that it does not close engagement gaps. Results contribute to theory about how digital media shape inequalities in news consumption and engagement.

Definitions of news are increasingly fraught in today’s media environment, making audience assessments of news-ness – the degree to which something is considered news – particularly important. Drawing from literature on representation in news and news-ness, we explore how seeing news that features a similar age group affects ratings of news-ness. We also argue that relevance offers as a psychological mechanism to explain how audiences make assessments about news-ness. Using two experiments among teens and adults in the United States, our results confirm that proximity (in terms of age) of the groups represented in news affects audience evaluations of news-ness, with relevance acting as a mediator to linking proximity and news-ness. These results are replicated across issues and among American teens and adults. We discuss the importance of representation and relevance as strategic initiatives to involve people in news.