  This paper presents the POLygraph dataset, a unique resource for fake news
detection in Polish. The dataset, created by an interdisciplinary team, is
composed of two parts: the "fake-or-not" dataset with 11,360 pairs of news
articles (identified by their URLs) and corresponding labels, and the
"fake-they-say" dataset with 5,082 news articles (identified by their URLs) and
tweets commenting on them. Unlike existing datasets, POLygraph encompasses a
variety of approaches from source literature, providing a comprehensive
resource for fake news detection. The data was collected through manual
annotation by expert and non-expert annotators. The project also developed a
software tool that uses advanced machine learning techniques to analyze the
data and determine content authenticity. The tool and dataset are expected to
benefit various entities, from public sector institutions to publishers and
fact-checking organizations. Further dataset exploration will foster fake news
detection and potentially stimulate the implementation of similar models in
other languages. The paper focuses on the creation and composition of the
dataset, so it does not include a detailed evaluation of the software tool for
content authenticity analysis, which is planned at a later stage of the
project.
