What Makes a High-Quality User-Generated Answer?

Blooma JOHN, Alton Chua, Dion Goh

Research output: Contribution to journalArticle

31 Citations (Scopus)

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. [ABSTRACT FROM AUTHOR] .
Original languageEnglish
Pages (from-to)66-71
Number of pages6
JournalIEEE Internet Computing
Volume15
Issue number1
DOIs
Publication statusPublished - 2011
Externally publishedYes

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