NwQM: A neural quality assessment framework for Wikipedia

• DOI: 10.18653/v1/2020.emnlp-main.674
• Publication Date: 2020-11-29T14:51:46Z
• Authors: Bhanu Prakash Red...; Sasi Bhushan Seel...; Soumya Sarkar; Animesh Mukherjee
• Keywords: Social and Information Networks (cs.SI); FOS: Computer and information sciences; 0202 electrical engineering, electronic engineering, information engineering; Computer Science - Social and Information Networks; Computer Science - Digital Libraries; Digital Libraries (cs.DL); 02 engineering and technology; 01 natural sciences; 0105 earth and related environmental sciences

EMNLP 2020: Long paper<br/>Millions of people irrespective of socioeconomic and demographic backgrounds, depend on Wikipedia articles everyday for keeping themselves informed regarding popular as well as obscure topics. Articles have been categorized by editors into several quality classes, which indicate their reliability as encyclopedic content. This manual designation is an onerous task because it necessitates profound knowledge about encyclopedic language, as well navigating circuitous set of wiki guidelines. In this paper we propose Neural wikipedia QualityMonitor (NwQM), a novel deep learning model which accumulates signals from several key information sources such as article text, meta data and images to obtain improved Wikipedia article representation. We present comparison of our approach against a plethora of available solutions and show 8% improvement over state-of-the-art approaches with detailed ablation studies.<br/>