News Verification: Conceptualization and Measurement


Student thesis: Doctoral Thesis

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Award date5 May 2022


Under the negative impact of fake news, a rising number of studies have investigated news verification, a news literacy behavior that may help combat it. After a systematic review of current studies on verification behaviors, however, a clear definition and measurement of news verification were not found. Therefore, this project aimed to conceptualize news verification and develop a valid measurement of it. The project defined news verification as actions to check if the news exists or if it is true and correct and highlighted the importance of clarifying the concept of news verification. Both quantitative and qualitative methods were used in the collection of items for a news verification scale. Data collected from the U.S. were used to examine a multidimensional model of news verification that contained three factors: content elements, social cues, and third-party sources. A scale of 12 items was finally established. Later, the model was examined using data collected from Sweden and China. The project also explored how news verification was correlated with other variables, such as news consumption, news literacy, and susceptibility to fake news. The project provides an in-depth understanding of news verification behaviors and a validated scale for future studies. The project suggests a promotion of news verification behaviors due to the public’s interest in, as well as the significance of, news, and the long-term benefits of practicing news verification: cultivating prudent and critical news audiences.