The SFU Opinion and Comments Corpus: A Corpus for the Analysis of Online News Comments

• Published in: Corpus pragmatics : international journal of corpus linguistics and pragmatics Vol. 4; no. 2; pp. 155 - 190
• Main Authors: Kolhatkar, Varada, Wu, Hanhan, Cavasso, Luca, Francis, Emilie, Shukla, Kavan, Taboada, Maite
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.06.2020
• Subjects: Computational Linguistics; Computer Appl. in Arts and Humanities; Linguistics; Original Paper; Pragmatics; Semantics; Social Sciences; Constructiveness; Negation; Toxicity; News discourse; Sentiment and opinion; Appraisal; Online comments
• ISSN: 2509-9507; 2509-9515; 2509-9515
• DOI: 10.1007/s41701-019-00065-w

We present the SFU Opinion and Comments Corpus (SOCC ), a collection of opinion articles and the comments posted in response to the articles. The articles include all the opinion pieces published in the Canadian newspaper The Globe and Mail in the 5-year period between 2012 and 2016, a total of 10,339 articles and 663,173 comments. SOCC is part of a project that investigates the linguistic characteristics of online comments. The corpus can be used to study a host of pragmatic phenomena. Among other aspects, researchers can explore: the connections between articles and comments; the connections of comments to each other; the types of topics discussed in comments; the nice (constructive) or mean (toxic) ways in which commenters respond to each other; how language is used to convey very specific types of evaluation; and how negation affects the interpretation of evaluative meaning in discourse. Our current focus is the study of constructiveness and evaluation in the comments. To that end, we have annotated a subset of the large corpus (1043 comments) with four layers of annotations: constructiveness, toxicity, negation and Appraisal (Martin and White, The language of evaluation, Palgrave, New York, 2005 ). This paper details our corpus, the data collection process, the characteristics of the corpus and describes the annotations. While our focus is comments posted in response to opinion news articles, the phenomena in this corpus are likely to be present in many commenting platforms: other news comments, comments and replies in fora such as Reddit, feedback on blogs, or YouTube comments.