An ML Model for Predicting Information Check-Worthiness using a Variety of Features

Ullah, Md Zia

Abstract

In this communication, we introduce the important problem of information check-worthiness. We present the method we developed to automatically answer this problem. This method makes use of an elaborated information representation that combines the “information nutritional label” features along with word-embedding features. The information check-worthy claim is then predicted by training a machine learning model based on these features. Our model outperforms the official participants’ runs of CheckThat! 2018 challenge.

Citation

Ullah, M. Z. (2020, February). An ML Model for Predicting Information Check-Worthiness using a Variety of Features. Presented at Workshop on Machine Learning for Trend and Weak Signal Detection in Social Networks and Social Media, Toulouse, France

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Workshop on Machine Learning for Trend and Weak Signal Detection in Social Networks and Social Media
• Start Date: Feb 27, 2020
• End Date: Feb 28, 2020
• Publication Date: 2020
• Deposit Date: Mar 22, 2023
• Publicly Available Date: Mar 22, 2023
• Volume: 2606
• Pages: 56-61
• Book Title: Proceedings of the Workshop on Machine Learning for Trend and Weak Signal Detection in Social Networks and Social Media
• Keywords: Information check-worthiness; Information nutritional label; Machine learning based mode
• Publisher URL: https://ceur-ws.org/Vol-2606/
• Related Public URLs: https://ceur-ws.org/Vol-2606/9paper.pdf