Analyzing Question Quality Through Intersubjectivity: World Views and Objective Assessments of Questions on Social Question-Answering
Social question-answering (SQA) allows people to ask questions in natural language and receive answers from others. While research on SQA has focused on the quality of answers provided with implications for system-based interventions, few studies have examined whether the questions asked to elicit these answers accurately depict an asker's information need. To address this gap, the current study explores the viability for system based interventions to improve questions by comparing human, non-textual assessments of question quality to automatic, textual features extracted from the questions' content in order to determine whether there is a significant relationship between subjective judgments on one hand, and objective ones on the other. Findings indicate that not only is there a significant relationship between human-based ratings of question quality criteria and extracted textual features, but also that …
Published in Proceedings of the 76th ASIS&T Annual Meeting: Beyond the Cloud: Rethinking Information Boundaries, 2013.
© Proceedings of the 76th ASIS&T Annual Meeting: Beyond the Cloud: Rethinking Information Boundaries 2013,
Kitzie, V., Choi, E., & Shah, C. (2013). Analyzing question quality through intersubjectivity: World views and objective assessments of questions on social question-answering. Proceedings Of The American Society For Information Science And Technology, 50(1), 1-10.