Stance Detection in Web and Social Media: A Comparative Study

July 12, 2020 · Entered Twilight · 🏛 Conference and Labs of the Evaluation Forum

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Repo contents: .gitignore, BERT.ipynb, CNN, KDEY, Preprocessing, README.md, SEN-SVM, Stance-detection-comparison-CLEF2019.pdf, TAN

Authors Shalmoli Ghosh, Prajwal Singhania, Siddharth Singh, Koustav Rudra, Saptarshi Ghosh arXiv ID 2007.05976 Category cs.CL: Computation & Language Cross-listed cs.LG Citations 84 Venue Conference and Labs of the Evaluation Forum Repository https://github.com/prajwal1210/Stance-Detection-in-Web-and-Social-Media ⭐ 31 Last Checked 1 month ago

Abstract

Online forums and social media platforms are increasingly being used to discuss topics of varying polarities where different people take different stances. Several methodologies for automatic stance detection from text have been proposed in literature. To our knowledge, there has not been any systematic investigation towards their reproducibility, and their comparative performances. In this work, we explore the reproducibility of several existing stance detection models, including both neural models and classical classifier-based models. Through experiments on two datasets -- (i)~the popular SemEval microblog dataset, and (ii)~a set of health-related online news articles -- we also perform a detailed comparative analysis of various methods and explore their shortcomings. Implementations of all algorithms discussed in this paper are available at https://github.com/prajwal1210/Stance-Detection-in-Web-and-Social-Media.