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A growing body of comparative studies on partisan hostility – a phenomenon known as affective polarization – is providing evidence that partisan affective polarization is generally no greater in the United States than it is in many European multiparty systems. This article takes the comparative literature on affective polarization one step further by presenting the first comparative study on affective polarization that simultaneously uses, compares and combines a direct measure of affective polarization towards voters (using the inter‐party marriage measure) and an indirect measure of affective polarization towards parties (using the like/dislike of party measure) while accounting for the fact that multiparty systems have numerous political parties. This is done by comparing the levels of affective polarization in the United States and Norway. The results show greater affective polarization in the United States relating to parties, but the differences between these two countries are indistinguishable from chance when focusing on the affect relating to voters. This provides empirical evidence that comparative evidence of negative affect towards parties cannot necessarily be generalized to suggest that there is comparative evidence of negative affect towards voters. Yet the results also suggest that negative feelings towards out‐parties move to some extent to the personal level in terms of negative feelings towards voters of these out‐parties.

This paper calls attention to what is arguably the most notable advancement in survey experiments over the last decade: conjoint designs. The benefit of conjoint design is its capacity to study and compare the causal effects of several dimensions simultaneously. Althoughsurveyexperimentshavelongbeenapreferredmethodforassessingcausaleffects, the method falls short when studying multidimensional causal relations. Researchers face a trade-off between a lack of statistical power or a restriction in experimental conditions. Conjoint designs solve this problem by letting the researcher vary an indefinite number of factors in one experiment. This method is quickly gaining ground in social and political science but has yet to be widely practiced in political communication research. This article argues that conjoint designs are ideal for studying political communication effects and highlights the possible benefits of using and innovating conjoint designs in political communication research. We make available sample scripts and demonstrate the value of this methodological technique through empirical examples of trust in news media and selective exposure to political news. ; publishedVersion

In this chapter, we focus on one of the most central issues within the scholarly literature on political communication: political media effects. We centre our discussion on the role played by the Nordic context for political media effects and focus on media effects on political learning and knowledge gaps; agenda-setting, priming, and framing effects; and media effects on voting and other political behaviours. Because much of the research and theories that have shaped the political communication literature on media effects emanate from the US, we discuss how differences between the American and the Nordic contexts may influence how well the theories of political media effects emanating from an American perspective fit the Nordic countries. We pay particular attention to studies related to the different theories that have been conducted in the Nordic context.

This article discusses a systematic process to determine whether to engage in collaborative software development of desktop applications in a government setting. Section One discusses collaboration and collaborative development. Then, after assessment of the strengths and weaknesses, a development team should have a better understanding for choosing a program-specific solution for collaborative development. Section Two assesses whether the conditions are favorable to pursue collaborative development for an existing project. An algorithm is provided for government agencies to gauge the success of collaborative development for a specific application. If a development team is able to (a) obtain copyright permission; (b) create an open development infrastructure; (c) pass through federal, organizational, and legal barriers; and (d) freely release the application's source code to the public, conditions may be favorable for collaborative development. Adapted from the source document.

AbstractReading or viewing recommendations are a common feature on modern media sites. What is shown to consumers as recommendations is nowadays often automatically determined by AI algorithms, typically with the goal of helping consumers discover relevant content more easily. However, the highlighting or filtering of information that comes with such recommendations may lead to undesired effects on consumers or even society, for example, when an algorithm leads to the creation of filter bubbles or amplifies the spread of misinformation. These well-documented phenomena create a need for improved mechanisms for responsible media recommendation, which avoid such negative effects of recommender systems. In this research note, we review the threats and challenges that may result from the use of automated media recommendation technology, and we outline possible steps to mitigate such undesired societal effects in the future.