Fine-grained Czech News Article Dataset: An Interdisciplinary Approach to Trustworthiness Analysis

Boháček, Matyáš; Bravanský, Michal; Filip, Trhlík,; Moravec, Václav

doi:10.48550/arxiv.2212.08550

Cited by 1 publication

(2 citation statements)

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“…A key development for the scientific community was the elimination of Twitter's free API tier by February 2023, to be replaced by a 'basic paid tier' 5 . For researchers and developers, this shift meant that Twitter content would no longer be available for research purposes without subscribing to a significantly different paid plan.…”

Section: Discussionmentioning

confidence: 99%

“…To better support and streamline the evaluation process, recent work has proposed automatic methods for estimating the publisher's trustworthiness based on the individual classification of news articles. The study in [5] considers four levels of trustworthiness and associates one of them with news articles in Czech. The work by Przybyla [24] chooses a binary classification (trustworthy vs. untrustworthy publisher) and achieves an average accuracy of 0.878 by classifying at the level of the news article.…”

Section: Related Workmentioning

confidence: 99%

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Unveiling News Publishers Trustworthiness Through Social Interactions

Pratelli,

Saracco,

Petrocchi

2024

ACM Web Science Conference

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With the primary goal of raising readers' awareness of misinformation phenomena, extensive efforts have been made by both academic institutions and independent organizations to develop methodologies for assessing the trustworthiness of online news publishers. Unfortunately, existing approaches are costly and face critical scalability challenges. This study presents a novel framework for assessing the trustworthiness of online news publishers using user interactions on social media platforms. The proposed methodology provides a versatile solution that serves the dual purpose of i) identifying verifiable online publishers and ii) automatically performing an initial estimation of the trustworthiness of previously unclassified online news outlets.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%