Dataset of controversial news posts in Spanish from the reader's perspective

Abstract

This paper presents a corpus of Spanish news posts obtained from X with the annotation of controversy made via crowdsourcing. A total of 60 tweets were obtained from 8 different newspapers. For the annotation task, a survey was developed and sent to 31 different participants to answer it with the controversy level they perceived from the news post summary and headline presented on the post. The most frequent selected option was assigned as the initial controversy level of the post. The final annotation of the corpus was made via an analysis of the raw data by computing the Inter Annotator Agreement (IAA). The analysis showed that the binarization of the data was the most convenient way to annotate it. A potential use for this dataset is detailed in further sections.

Keywords

• News controversy
• News articles
• X data
• Readers perspective