May 21, 2024 · In this paper, we analyse the trustworthiness of online news media outlets by leveraging a dataset of 4033 news stories from 40 different sources.
Jan 3, 2024 · In this paper, we analyse the trustworthiness of online news media outlets by leveraging a dataset of 4033 news stories from 40 different sources.
The results indicate that the classification model is highly effective in classifying the trustworthiness levels of the news articles and has practical ...
Evaluating Trustworthiness of Online News Publishers via Article Classification ; John Bianchi. IMT School for Advanced Studies Lucca. Italy ; Manuel Pratelli.
May 25, 2024 · This study uses a standard dataset with features relating to the credibility of news publishers. These features are analysed using each of these algorithms.
Evaluating Trustworthiness of Online News Publishers via Article Classification. https://doi.org/10.1145/3605098.3636044. Journal: Proceedings of the 39th ACM ...
May 21, 2024 · This study presents a novel framework for assessing the trustworthiness of online news publishers using user interactions on social media platforms.
Missing: Evaluating | Show results with:Evaluating
Trust assessment studies performed on article-based sources tend to use content- based features (e.g., article length), since often the author is unknown, while.
We found that reliable news articles have a higher proportion of neutral sentiment, while unreliable articles have a higher proportion of negative sentiment.
Aug 17, 2023 · In this paper, we use a bottom-up approach to understand how people evaluate the trustworthiness of online news. ... Access journal content via a ...