Despite the scholarly popularity of important developments of political communication, concepts like soft news or infotainment lack conceptual clarity. This article tackles that problem and introduces a multilevel framework model of softening of journalistic political communication, which shows that the 4 most prominent concepts—(a) sensationalism, (b) hard and soft news (HSN), (c) infotainment, and (d) tabloidization, and, additionally, (e) eroding of boundaries of journalism—can be distinguished in a hierarchical model. By softening, we understand a metaconcept representing developments in political journalism that are observed on different levels of investigation, from journalism as a system (macrolevel) down to single media items (microlevel).

This article critically examines long-term media effects in communication research. Focusing on news exposure, the purpose is to provide a review and theoretical conceptualization of long-term effects on societal beliefs. The first part presents an empirical overview of research published in leading communication journals. While longitudinal studies are not uncommon, few have an explicit and elaborated focus on long-term influences. To advance future research, the second part builds on cognitive schema theory to develop three distinct ways of conceptualizing long-term effects: in terms of (a) effect duration, (b) effect mechanisms and (c) effect dynamics. Finally, the third part condenses a comprehensive literature review into a multilevel framework model of factors contributing to long-term media effects on societal beliefs.

Despite the popularity of the concept of hard and soft news, researchers regularly criticize the vague definitions and inconsistent conceptualizations. Following claims for standardization of concept in journalism research, this article aims to cross-validate the most recent understanding of the concept. We conducted a factorial survey with newspaper journalists to probe the question as to which of the theoretically assumed dimensions of the concept are referred to by journalists to distinguish hard from soft news. We find the dimensions “topic,” “relevance,” “framing,” and “opinion” to exert influence on journalists’ understanding of the concept.

We introduce a design that is able to face some of the challenges that digital news consumption is posing to traditional media effects methods like linkage analysis. The challenges include (1) memory errors and biases when reporting everyday news media consumption leading to (2) errors when linking mass media outlets to survey data; (3) personalization of media content, as well as (4) short-term dynamic processes. Mobile Intensive Longitudinal Linkage Analysis (MILLA) uses an innovative combination of smartphone data donations to capture media exposure and relevant media content, a mobile experience sampling questionnaire to capture immediate reactions to news, and the content analysis of uploaded news media content to measure media effects. The design is explained by using an example of negativity in the news and its effects on emotional reactions of recipients.

This paper advances the research on personalization of political communication by investigating whether this process of focusing on politicians instead of political issues plays a role on Twitter. Results of a content analysis of 5,530 tweets posted in the run-up to the German federal election provide evidence that Twitter communication refers more often to politicians than to issues. However, tweets containing personal characteristics about political leaders play only a marginal role. When distinguishing among different groups of actors on Twitter (journalists, politicians, citizens), we find that citizens focus more on candidates than do journalists or politicians. Investigating the impact of a televised debate on Twitter communication, we observe that this person-centered event puts the focus on individual politicians instead of issues.