2017/03/11 by Suman Kalyan Maity, Maity, Suman Kalyan, Aman Kharb +3 · 1 citation
Computer Science · #Computation and Language (cs.CL) #Expert finding and Q&A systems #FOS: Computer and information sciences #Social and Information Networks (cs.SI) #Topic Modeling
paper · pdf · doi:10.48550/arxiv.1703.04001
openalex publication_date 2017/03/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Quora is one of the most popular community Q&A sites of recent times.\nHowever, many question posts on this Q&A site often do not get answered. In\nthis paper, we quantify various linguistic activities that discriminates an\nanswered question from an unanswered one. Our central finding is that the way\nusers use language while writing the question text can be a very effective\nmeans to characterize answerability. This characterization helps us to predict\nearly if a question remaining unanswered for a specific time period t will\neventually be answered or not and achieve an accuracy of 76.26% (t = 1 month)\nand 68.33% (t = 3 months). Notably, features representing the language use\npatterns of the users are most discriminative and alone account for an accuracy\nof 74.18%. We also compare our method with some of the similar works (Dror et\nal., Yang et al.) achieving a maximum improvement of ~39% in terms of accuracy.\n