Journalists and experts play a pivotal role in communicating risks and helping the public navigate uncertain futures. This study examines the co-construction of projections by journalists and experts across news and social media during the Covid-19 pandemic. Unlike traditional news production, where journalists exercise agency by transforming expert knowledge into news narratives, hybrid media environments involve multi-platform, multi-directional, and non-linear processes of knowledge production. In light of these characteristics, we introduce and develop the concept of “predictive agency,” referring to an actor’s active participation in predictive knowledge-making and encompassing journalistic, civic, and epistemic forms of agency in shaping and navigating future-oriented knowledge. We analyse the trajectories of 400 projections in Israel and the US, tracing the interactional and informational dynamics between journalists and experts. Through qualitative textual analysis of the various iterations of each projection, four types of co-constructed projection systems emerge: Amplify, Distill, Elaborate, and Contest. We explore the complexities of predictive agency and accountability in these systems, shedding light on how collective futures are contested and co-constructed in hybrid media environments.

Communication research has long explored the association between media trust and news consumption. However, the strength and direction of this relationship have remained elusive. This study suggests a new approach for investigating these complex relations, differentiating between usage and trust associated with different sources over time. Focusing on the 2022 French election and drawing on data from a four-wave panel survey (N = 1,294), we utilized Random Intercept Cross-Lagged Panel Model (RI-CLPM) analysis to uncover two key over time effects: a selection effect, wherein trust reinforces usage; and a media effect, wherein usage influences trust. While a selection effect driven by news trust was observed in a right-wing political alternative channel, a media effect leading to news trust was linked with more traditional television channels. By identifying these effects and their associations with various types of outlets, this study advances the ongoing scholarly debate around the role of trust in news consumption.

Research on trust has come to the forefront of communication studies. Beyond the dominant focus on informational trust and its country-specific articulations, trustworthiness evaluations can relate to the materiality of news and its global manifestations. Especially in digital algorithmic environments, understanding news trustworthiness requires a holistic approach, which combines informational and socio-technical aspects while addressing both institutional and interpersonal trust. Drawing on 488 in-depth interviews with media consumers in Argentina, Finland, Israel, Japan, and the United States, this article investigates news (dis)trust from the lens of socio-materiality. The six trust-oriented affordances we identified—selectivity, interactivity, customization, searchability, information abundance, and immediacy—reveal important socio-technical commonalities that underlie news trust across countries. These affordances, moreover, point to an interplay of trust and self-agency. Taken together, the findings illuminate the lived experience of news trust as manifested across cultures and offer a broader understanding of trustworthiness within current media ecology.

How do religious citizens’ election projections influence voter turnout? While previous studies have demonstrated the significant impact of religious orientation on individuals’ general future outlook, little is known about the influence of religion on voters’ electoral expectations and how these expectations affect voter turnout. In this paper, we employ a nuanced conceptual framework of election projections and examine the impact of religion on both the affective and probabilistic aspects of citizens’ expectations regarding election outcomes. Our analysis draws upon original panel survey data collected in two countries, focusing on the 2021 Israeli general elections and the 2022 French presidential elections. The findings reveal a mobilizing effect of religious citizens’ election projections in both Israel and France. Specifically, religious voters tend to have more positive affective forecasts about their projected election outcomes, consequently resulting in increased voter turnout. While affective forecasting plays a significant role in religious citizens’ turnout, probabilistic certitude does not have a similar effect. We discuss the contribution and implications of these findings for research on religion and political behavior.

In an era of information overload, understanding individuals’ news consumption and avoidance necessitates an examination of the specific contexts in which these practices occur. While research in journalism studies has mainly underscored consumption habits at the individual level, limited scholarly attention has been given to news avoidance within the structure of dyadic spousal relationships. This study shifts the focus from individual choices to the couple as a unit of analysis, exploring how each partner’s choice of media platform, content, and routines may be shaped by the context of being in a spousal relationship. Drawing on 82 interviews with Israelis, including 14 interviews with both partners of seven heterosexual couples, this study reveals three patterns of news avoidance within the context of a couple’s relationship: avoiding shared news consumption, gender-based news avoidance practices, and a division of media-related responsibilities. This study contributes to a more nuanced understanding of the contextual factors shaping news avoidance by elucidating how media use and non-use unfold within social relationships. It also demonstrates how news avoidance can be perceived as a liberating choice, enabled by partners’ negotiation of preferences, platforms, and routines.

One of us (dre) is a fan of The Who. Part of the refrain from one of their hits is “Well, who are you? I really wanna know. Tell me, who are you?” Long hours were spent during adolescence pondering this question. Now this question is being pondered again regarding the discipline. The question of “who are you?” is a question that has historically plagued our discipline. And it is a question that one contemplates when taking on the editorship of the Journal of Communication (JoC). Historically, our answer to the question “Who are you?” has been that we are an extremely eclectic group of scholars united by a broad interest in communication. Ironically, however, communication scholars have often been reluctant to communicate with other communication scholars. Regrettably, our culture is one of distinct “camps,” which are making amazing progress in their self-defined areas of research, although talk across areas is severely limited (Tenenboim-Weinblatt & Lee, 2020), and different camps often disparage each other’s approaches to epistemology.¹ This is an unfortunate situation because for us our diversity is one of the intellectual strengths of this discipline (Ewoldsen, 2023).

In this paper, we propose a new strategy for classifying evaluations in large text corpora, using supervised machine learning (SML). Departing from a conceptual and methodological critique of the use of sentiment measures to recognize object-specific evaluations, we argue that a key challenge consists in determining whether a semantic relationship exists between evaluative expressions and evaluated objects. Regarding sentiment terms as merely potentially evaluative expressions, we thus use a SML classifier to decide whether recognized terms have an evaluative function in relation to the evaluated object. We train and test our classifier on a corpus of 10,004 segments of election coverage from 16 major U.S. news outlets and Tweets by 10 prominent U.S. politicians and journalists. Specifically, we focus on evaluations of political predictions about the outcomes and implications of the 2016 and 2020 U.S. presidential elections. We show that our classifier consistently outperforms both off-the-shelf sentiment tools and a pre-trained transformer-based sentiment classifier. Critically, our classifier correctly discards numerous non-evaluative uses of common sentiment terms, whose inclusion in conventional analyses generates large amounts of false positives. We discuss contributions of our approach to the measurement of object-specific evaluations and highlight challenges for future research.

This paper explores trust-building strategies in future-oriented news discourse, marked by a high degree of uncertainty. While current research mainly focuses on audiences’ perceptions of news credibility, this study addresses news trust from a production standpoint. We examine the trust-building efforts of media actors, focusing on their discursive labor within the context of election projections. Drawing on rich data from five election rounds in Israel and the US, we qualitatively analyzed 400 news texts and 400 tweets that were produced by 20 US and 20 Israeli media actors. This textual analysis was supplemented by 10 in-depth interviews with Israeli journalists. Our findings demonstrate three types of journalistic trust-building rhetoric in election coverage: facticity, authority, and transparency. These strategies result in a two-fold form of trust, which re-affirms traditional notions of accuracy and validity, while also challenging the ability of newspersons to obtain them in contemporary political and media cultures. Overall, these strategies hold unique opportunities and challenges for sustaining public trust in journalism and illuminate the complex communicative labor involved in building trust with news audiences. Our findings also highlight the importance of studying trust not only in relation to the past and the present, but also in future-oriented discourse.

How and why do people still get print newspapers in an era dominated by mobile and social media communication? In this article, we answer this question about the permanence of traditional media in a digital media ecosystem by analyzing 488 semi-structured interviews conducted in Argentina, Finland, Israel, Japan, and the United States. We focus on three mechanisms of media reception: access, sociality, and ritualization. Our findings show that these mechanisms are decisively shaped by patterns of everyday life that are not captured by the scholarly foci on either content- or technology-influences on media use. Thus, we argue that a non-media centric approach improves descriptive fit and adds heuristic power by bringing a wider lens into crucial mechanisms of media reception in ways that expand the conceptual toolkit that scholars can utilize to analyze the role of media in everyday life.

This chapter examines the social dynamics of projections about the outcomes and implications of the repeated elections in Israel. Based on a combination of a panel survey and focus groups, we analyze citizens’ evolving predictions regarding the expected largest party, the next prime minister, the coalition composition, and the future of Israel more generally. Introducing a conceptual framework that breaks political projections into several constituent elements, we study what probabilities and evaluations people assign to their predictions, how they explain them, and what their implications are for political participation. We show that despite the deepening political crisis, Israeli citizens’ political optimism did not decrease during the three 2019–2020 election campaigns. Furthermore, we find an important link between intention to vote and the expected level of happiness about the predicted outcomes. Based on these findings, we argue that persistent optimism is one explanation for the higher voter turnout in each round of elections. In the epilogue we consider additional insights from the 2021 election, which saw a reversal in voters’ growing optimism and turnout, but which eventually fulfilled hopes of the anti-Netanyahu camp for political change.