Disentangling the Influence of Recommender Attributes and News-Story Attributes: A Conjoint Experiment on Exposure and Sharing Decisions on Social Networking Sites

While news outlets still play an important role as a source of news, people increasingly receive their political information and news from social networking sites (SNSs). This study extends the literature on exposure and sharing decisions on SNSs by exploring how different attributes shape such decisions, how the two decision types differ, and by disentangling the role played by personal news recommendations and shared news stories on SNSs. As SNSs add a social dimension, exposure and sharing decisions are contingent not only upon the news story itself (news-story attributes) but also upon characteristics of the person who shares the story (recommender attributes). We designed a conjoint experiment to disentangle the effects of recommender and news-story attributes on the decision to recommend and read news and fielded it in a probability-based Norwegian online survey. The results suggest that committing to reading and sharing information are two similar yet distinct phenomena and that selective sharing is a stronger commitment than selective exposure. We also found evidence to suggest that selective sharing of news featuring a favored political party was contingent upon whether one also received information about the recommender attributes.publishedVersio

How the public understands news media trust: An open-ended approach

Despite the central role that ordinary citizens play as ‘trustors’ (i.e. the actor that places trust) in the literature on news media trust, prior quantitative studies have paid little attention to how ordinary citizens understand and define news media trust. Here, trust tends to be studied from a researcher-defined – rather than an audience-defined – perspective. To address this gap, we investigate how the public describes news media trust in their own words by asking them directly. We analyse 1500 written responses collected through a Norwegian online probability-based survey, here using a semisupervised quantitative text analysis technique called structural topic modelling (STM). We find that citizens’ own understanding of news media trust can be categorised into four distinct topics that, in some instances, are comparable to academic and professional discourse. We show that citizens’ written descriptions of news media trust vary by many of the same variables that prior research has found to be important predictors of levels of trust. Respondents’ written descriptions of news media trust vary by education and satisfaction with democracy but not other known predictors of trust, such as ideological self-placement and political preferences.publishedVersio