Trust and Journalistic Transparency Online

Koliska, Michael

doi:10.1080/1461670x.2022.2102532

Cited by 17 publications

(19 citation statements)

References 46 publications

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“…Despite the strong scholarly interest in transparency and its proposed effects on trust and credibility, only few studies have investigated these effects empirically (Curry and Stroud, 2019; Karlsson et al, 2014; Koliska, 2015; Masullo et al, 2021; Meier and Reimer, 2011; Tandoc and Thomas, 2017). Moreover, these studies share several features that make an accumulation of evidence challenging: They (1) show strong conceptual differences regarding the main dependent variable, (2) investigate vastly differing transparency tools, (3) handle the challenges of designing media effects experiments contrastingly, and (4) have only started to systematically investigate the effects of moderating factors.…”

Section: Literature Review: Transparency In Journalismmentioning

confidence: 99%

“…One central problem of media trust and credibility research is that the two terms are often used interchangeably (Engelke et al, 2019; Kohring and Matthes, 2007). Some transparency studies (Koliska, 2015; Meier and Reimer, 2011) employ instruments that measure trust in journalism and conceptualize credibility as a subset of trust (Kohring and Matthes, 2007). Other studies (Curry and Stroud, 2019; Karlsson et al, 2014; Masullo et al, 2021; Tandoc and Thomas, 2017) aim at measuring transparency’s effects on credibility.…”

Section: Literature Review: Transparency In Journalismmentioning

confidence: 99%

“…Only two (information about the motivation of a story and links) were related to the tools tested by Karlsson et al (2014). Meier and Reimer (2011) as well as Koliska (2015) took yet another approach and differentiated between producer and production transparency. The former was implemented by information about the author and contact information while the latter consisted of additional information about sources and documents articles were based on.…”

Section: Literature Review: Transparency In Journalismmentioning

confidence: 99%

“…Empirical research about transparency’s effects on audience perceptions is scarce (Curry and Stroud, 2019; Karlsson et al, 2014; Koliska, 2015; Masullo et al, 2021; Meier and Reimer, 2011; Tandoc and Thomas, 2017). In this paper, we are interested in the effects of additional information about the author and information about the research that went into the article.…”

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confidence: 99%

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The more, the better? Effects of transparency tools and moderators on the perceived credibility of news articles

2021

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Transparency is often discussed as a way to increase the public’s perception of journalism. While its adoption by newsrooms is relatively well studied, only a few studies have investigated its effects on news users’ credibility judgments. We build on research about transparency effects and report the results of two online experiments (total N = 2262), one with a local and one with a national newspaper frame. Our results suggest that transparency does not affect the perceived message and source credibility newspaper articles and that moderating factors such as cognitive involvement and media skepticism are more important predictors of credibility assessments.

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Section: Literature Review: Transparency In Journalismmentioning

confidence: 99%

Section: Literature Review: Transparency In Journalismmentioning

confidence: 99%

Section: Literature Review: Transparency In Journalismmentioning

confidence: 99%

mentioning

confidence: 99%

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The more, the better? Effects of transparency tools and moderators on the perceived credibility of news articles

2021

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“…An interview set-up might be insufficient to uncover actual strategies and decision-making processes: quoting, like other routine work, is most likely conducted on auto-pilot, to alleviate the cognitive strain brought about by the hectic nature of news work. There is also the possibility that journalists will intentionally or sub-consciously dress up practices that breach guidelines or social norms (Koliska, 2015: section 8.3).…”

Section: Introductionmentioning

confidence: 99%

Etic and emic data production methods in the study of journalistic work practices: A systematic literature review

Haapanen

Manninen

2021

Journalism

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This methodological paper discusses the application of etic and emic perspectives in producing data sets for the study of journalistic praxis. The concepts refer to the researcher-analyst’s and the practitioner-informant’s viewpoints, respectively, and that being the case, they have inherent weaknesses if used independently. We argue that these shortcomings can be mitigated through an integrated application of the concepts and by seeing the two perspectives as complementary to each other. Combining etic and emic perspectives will allow for a more comprehensive understanding of complex yet routinized real-life behaviour such as journalistic work. Following the appraisal of the etic-emic combination methodology, we present the results of a systematic literature review. We explore the application of this methodology in the study of journalistic work, as recounted in international journal articles published between 2000 and 2017. After keyword searches into several databases and a manual review of 3018 items, a corpus of 228 relevant articles was analysed. Our results demonstrate the studies’ disproportionate emphasis on the earliest phases of the journalistic process, that is, topic discovery, topic selection, point of view selection and sourcing, and the relative scarcity of studies applying a fully integrated etic-emic-combination methodology. We also report on, for example, the types of research material used and the media studied. We conclude with recommendations for expanding and diversifying the use of etic-emic-combination methodology in journalism studies to give us a more balanced understanding of the field.

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A data-centric approach for ethical and trustworthy AI in journalism

Dierickx,

Opdahl,

Khan

et al. 2024

Ethics Inf Technol

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AI-driven journalism refers to various methods and tools for gathering, verifying, producing, and distributing news information. Their potential is to extend human capabilities and create new forms of augmented journalism. Although scholars agreed on the necessity to embed journalistic values in these systems to make AI systems accountable, less attention was paid to data quality, while the results’ accuracy and efficiency depend on high-quality data in any machine learning task. Assessing data quality in the context of AI-driven journalism requires a broader and interdisciplinary approach, relying on the challenges of data quality in machine learning and the ethical challenges of using machine learning in journalism. To better identify these, we propose a data quality assessment framework to support the collection and pre-processing stages in machine learning. It relies on three of the core principles of ethical journalism—accuracy, fairness, and transparency—and participates in the shift from model-centric to data-centric AI, by focusing on data quality to reduce reliance on large datasets with errors, making data labelling consistent, and better integrating journalistic knowledge.

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Trust and Journalistic Transparency Online

Cited by 17 publications

References 46 publications

The more, the better? Effects of transparency tools and moderators on the perceived credibility of news articles

The more, the better? Effects of transparency tools and moderators on the perceived credibility of news articles

Etic and emic data production methods in the study of journalistic work practices: A systematic literature review

A data-centric approach for ethical and trustworthy AI in journalism

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