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HOW TO UNDERSTAND TRUST IN NEWS MEDIA – A THEORETICAL MODEL

Abstract

Trust in news media is critical in the everyday workings of a living democracy. However, several studies indicate that this trust is low or dwindling. Little is also known about how to understand and measure trust in this new and multifaceted media landscape. The objective of this paper is, therefore, to develop a theoretical model for understanding the components and nature of trust in news media, and show how professionals can use this model to predict and evaluate trust. The model is a modified version of Mayer, Davis, and Schoorman’s (1995) well-known model of interpersonal trust in organizations. Their model was one of the first to conceptualize trust as a dynamic and multidimensional concept, where trust is seen as particularly relevant for circumstances characterized by perceived risk. Due to significant changes in patterns of news consumption, we acknowledge and study how trust and trust antecedents vary across news organizations and different social contexts. In addition, our model of trust address a digital context with increasingly fragmented news media outlets, user groups, and changing media habits. The purpose of the proposed theoretical model is to adequately reflect citizen-diversity with factors determining specific "news media user types", and subsequently be able to examine user types as a moderating construct on trust and the trust antecedents. We address three different layers of factors that are likely to determine the type of news media users, such as individual attitudes or political preference, social or organizational networks, and culture or society.

Category

Academic lecture

Client

  • Research Council of Norway (RCN) / 262848

Language

English

Author(s)

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies
  • University of Oslo

Presented at

2017 Association of Internet Researchers Conference Networked Publics

Place

Tartu

Date

18.10.2017 - 21.10.2017

Organizer

Association of Internet Researchers Conference

Year

2017

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