Institut für Kommunikationswissenschaft

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    How news audiences allocate trust in the digital age: A figuration perspective
    (2024) Mangold, Frank; Bachl, Marko; Prochazka, Fabian; Mangold, Frank; GESIS—Leibniz Institute for the Social Sciences, Köln, Germany; Bachl, Marko; University of Hohenheim, Stuttgart, Germany; Prochazka, Fabian; University of Erfurt, Germany
    The article enriches the understanding of trust in news at a time when mass and interpersonal communication have merged in the digital sphere. We propose disentangling individual-level patterns of trust allocation (i.e., trust figurations ) across journalistic media, social media, and peers to reflect the multiplicity among modern news audiences. A latent class analysis of a representative survey among German young adults revealed four figurations: traditionalists, indifferentials, optimists, and cynics. Political characteristics and education corresponded with substantial heterogeneity in individuals’ trust in news sources, their inclination to differentiate between sources, and the ways of integrating trust in journalistic and non-journalistic sources.
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    Response Item Network (ResIN): A network-based approach to explore attitude systems
    (2024) Carpentras, Dino; Lueders, Adrian; Quayle, Michael; Carpentras, Dino; Computational Social Science, ETH Zürich, Zürich, Switzerland; Lueders, Adrian; Department of Communication Science, University of Hohenheim, Stuttgart, Germany; Quayle, Michael; Department of Psychology, University of Limerick, Limerick, Ireland
    Belief network analysis (BNA) refers to a class of methods designed to detect and outline structural organizations of complex attitude systems. BNA can be used to analyze attitude-structures of abstract concepts such as ideologies, worldviews, and norm systems that inform how people perceive and navigate the world. The present manuscript presents a formal specification of the Response-Item Network (or ResIN), a new methodological approach that advances BNA in at least two important ways. First, ResIN allows for the detection of attitude asymmetries between different groups, improving the applicability and validity of BNA in research contexts that focus on intergroup differences and/or relationships. Second, ResIN’s networks include a spatial component that is directly connected to item response theory (IRT). This allows for access to latent space information in which each attitude (i.e. each response option across items in a survey) is positioned in relation to the core dimension(s) of group structure, revealing non-linearities and allowing for a more contextual and holistic interpretation of the attitudes network. To validate the effectiveness of ResIN, we develop a mathematical model and apply ResIN to both simulated and real data. Furthermore, we compare these results to existing methods of BNA and IRT. When used to analyze partisan belief-networks in the US-American political context, ResIN was able to reliably distinguish Democrat and Republican attitudes, even in highly asymmetrical attitude systems. These results demonstrate the utility of ResIN as a powerful tool for the analysis of complex attitude systems and contribute to the advancement of BNA.