Classifying news versus opinions in newspapers: Linguistic features for domain independence. (21st February 2017)

• Record Type: Journal Article
• Authors: KRÜGER, K. R.; LUKOWIAK, A.; SONNTAG, J.; WARZECHA, S.; STEDE, M.
• Is Part Of: Natural language engineering. Volume 23:Part 5(2017)
• Page Start: 687
• Page End: 707
• Publication Date: 2017-02-21
• Subjects: Natural language processing (Computer science) -- Periodicals; Software engineering -- Periodicals; 006.35
• DOI: 10.1017/S1351324917000043
• Languages: English
• ISSNs: 1351-3249

Abstract

Abstract: Newspaper text can be broadly divided in the classes 'opinion' (editorials, commentary, letters to the editor) and 'neutral' (reports). We describe a classification system for performing this separation, which uses a set of linguistically motivated features. Working with various English newspaper corpora, we demonstrate that it significantly outperforms bag-of-lemma and PoS-tag models. We conclude that the linguistic features constitute the best method for achieving robustness against change of newspaper or domain.