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We present a novel corpus for subjectivity detection at the sentence level.We develop new annotation guidelines for the task, which are not limited tolanguage-specific cues, and apply them to produce a new corpus in English. Thecorpus consists of 411 subjective and 638 objective sentences extracted fromongoing coverage of political affairs from online news outlets. This newresource paves the way for the development of models for subjectivity detectionin English and across other languages, without relying on language-specifictools like lexicons or machine translation. We evaluate state-of-the-artmultilingual transformer-based models on the task, both in mono- andcross-lingual settings, the latter with a similar existing corpus in Italianlanguage. We observe that enriching our corpus with resources in otherlanguages improves the results on the task.

A Corpus for Sentence-level Subjectivity Detection on English News Articles