Knowledge fixation and accretion: longitudinal analysis of a social question-answering site
Article publication date: 2 September 2014
The purpose of this paper is to investigate longitudinal features of an established social question-answering (Q&A) site to study how question-answer resources and other community features change over time.
Statistical analysis and visualisation was performed on the full data dump from the Stack Overflow social Q&A site for programmers.
The timing of answers is as strong a predictor of acceptance – a proxy for user satisfaction – as the structural features of provided answers sometimes associated with quality. While many questions and answer exchanges are short-lived, there is a small yet interesting subset of questions where new answers receive community approval and which may end up being ranked more highly than early answers.
As a large-scale data oriented research study, this work says little about user motivations to find and contribute new knowledge to old questions or about the impact of the resource on the consumer. This will require complementary studies using qualitative and evaluative methods.
While content contribution to social question-asking is largely undertaken within a very short time frame, content consumption is usually over far longer periods. Methods and incentives by which content can be updated and maintained need to be considered. This work should be of interest to knowledge exchange community designers and managers.
Few studies have looked at temporal patterns in social Q&A and how time and the moderation and voting systems employed may shape resource quality.
This work was supported by the Faculty of Environment and Technology, University of the West of England. The author wishes to thank the reviewers for their constructive feedback.
Matthews, P. (2014), "Knowledge fixation and accretion: longitudinal analysis of a social question-answering site", Journal of Documentation, Vol. 70 No. 5, pp. 711-733. https://doi.org/10.1108/JD-04-2013-0050
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