Suchergebnisse

"This chapter discusses the state of the art in research on the interplay between mass mediated and interpersonal political communication. After giving basic definitions, direct and mediated effects of political talk on various outcomes (e.g., knowledge, attitudes, participation) are discussed on the basis of several key models (e.g., mediation model, O-S-R-O-R model). Generally, it is argued that the Internet has renewed scholarly interest in the issue but that most studies still investigate interpersonal or mass communication separately, largely neglecting the other mode of communication. Only recently researchers have begun to more explicitly address the interplay between interpersonal and mass mediated political communication. Therefore, the chapter calls for a more thorough theoretical and empirical integration of interpersonal and mass communication perspectives in political communication research." (publisher's description)

The COVID-19 pandemic has led to a rise in opposition to vaccination, hindering herd immunity. As social media play a major role in the formation of anti-vaccination communities, it is critical to monitor the discourse on the platforms to effectively counter the negative sentiment and encourage people to vaccinate. This study employs computational content analysis, specifically topic modeling and time series analysis, to monitor the COVID-19 anti-vaccination communities on Facebook in Czechia. The analysis generated 18 topics with politics, governance, and international affairs being the most discussed, and only five dealt with issues directly related to COVID-19. Discussions about information and its credibility were prevalent, and members of these anti-vaccination communities relied heavily on social media content and conspiracy websites as sources of information, while neglecting scientific resources. The study highlights the need for ongoing monitoring of anti-vaccination communities on social media and the development of effective communication strategies to promote vaccination.

The possibly detrimental consequences of soft news are subject of popular and academic debate. This study investigates how watching particular news genres—soft versus hard—relates to cynicism about politics among Dutch citizens. A nuanced and novel scale measuring relative exposure to soft versus hard news is introduced using nonparametric unidimensional unfolding. The analysis of three public opinion surveys demonstrates a strong relationship between people's position on this hard versus soft news exposure scale and political cynicism. People who watched relatively more soft news were more cynical about politics than people who watched relatively more hard news. This relationship was not conditional on individuals' level of political knowledge and interest.

"Nachrichten-Bias spielt in Zeiten des Wahlkampfes mutmaßlich eine wichtige Rolle. Die vorliegende Studie beschäftigt sich mit den Auswirkungen von Nachrichten-Bias auf das Wahlverhalten. Es werden zwei unterschiedliche Formen von Nachrichten-Bias vorgestellt, und es wird den Fragen nachgegangen, (1) ob es einen Zusammenhang zwischen subjektivem und objektivem Nachrichten-Bias gibt und (2) ob diese Formen von Nachrichten-Bias die Wahlentscheidung beeinflussen. Die Ergebnisse legen nahe, dass es nur einen geringfügigen Zusammenhang zwischen objektivem und subjektivem Bias gibt. Es zeigt sich überdies, dass der subjektive Bias keine Auswirkungen auf die Wahlentscheidung hat, wohl aber die Sichtbarkeit von Parteien in den Medien und der Tenor der Berichterstattung." (Autorenreferat)

This is a response to Pauwels' critique of our 2007 Electoral Studies article about the relationship between media content and anti-immigrant party support. We argue here, that Pauwels' criticism falls short in three respects: (1) it is based on a selective presentation of our and others' arguments; (2) it fails to distinguish between cross-sectional and longitudinal explanations of anti-immigrant party support; and (3) it presents an overly simplified re-analysis which fails to take into account the dynamic properties of the time-series. Certainly, Pauwels' article contains some interesting suggestions for future research, but his assessment offers no strong evidence for a different interpretation of the relationship between media and anti-immigrant party support than the one given in our original article. Pauwels presents selective arguments. The critique fails to distinguish cross-sectional and time-series analysis.The article presents an overly simple re-analysis. [Copyright Elsevier Ltd.]

AbstractImmigration is an increasingly important political issue in Western democracies and a crucial question relates to the antecedents of public attitudes towards immigrants. It is generally acknowledged that information relayed through the mass media plays a role in the formation of anti‐immigration attitudes. This study considers whether news coverage of immigrants and immigration issues relates to macro‐level dynamics of anti‐immigration attitudes. It further explores whether this relationship depends on variation in relevant real world contexts. The models simultaneously control for the effects of established contextual explanatory variables. Drawing on German monthly time‐series data and on ARIMA time‐series modeling techniques, it is shown that both the frequency and the tone of coverage of immigrant actors in the news significantly influence dynamics in anti‐immigration attitudes. The strength of the effect of the news, however, depends on contextual variation in immigration levels and the number of asylum seekers. Implications of these findings are discussed in the light of the increasing success of extreme right parties and growing opposition to further European integration.