Scalable Visualisation of Sentiment and Stance

Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

Abstract

Natural language processing systems have the ability to analyse not only the sentiment of human language, but also the stance of the speaker. Representing this information visually from unevenly distributed and potentially sparse datasets is challenging, in particular when trying to facilitate exploration and knowledge discovery. We present work on a novel visualisation approach for scalable visualisation of sentiment and stance and provide a language resource of e-government public engagement of 9,278 user comments with stance explicitly declared by the author.