Title :
What Makes a High-Quality User-Generated Answer?
Author :
John, Blooma Mohan ; Chua, Alton Yeow-Kuan ; Goh, Dion Hoe-Lian
Author_Institution :
Nanyang TechnologicalUniversity, Nanyang, China
Abstract :
Community-driven question-answering (CQA) services on the Internet let users share content in the form of questions and answers. Usually, questions attract multiple answers of varying quality from other users. A new approach aims to identify high-quality answers from candidate answers to questions that are semantically similar to the new question. Toward that end, the authors developed and tested a quality framework comprising social, textual, and content-appraisal features of user-generated answers in CQA services. Logistic-regression analysis revealed that content-appraisal features were the strongest predictor of quality. These features include dimensions such as comprehensiveness, truthfulness, and practicality.
Keywords :
Internet; question answering (information retrieval); regression analysis; user interfaces; Internet; community-driven question-answering service; content-appraisal quality feature; high-quality user-generated answer; logistic-regression analysis; quality framework; social quality feature; textual quality feature; Accuracy; Feature extraction; Internet; Social network services; User interfaces; Web services; Internet; quality framework; question answering;
Journal_Title :
Internet Computing, IEEE
DOI :
10.1109/MIC.2011.23
