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Who will answer my question on Stack Overflow?

conference contribution
posted on 2015-01-01, 00:00 authored by M Choetkiertikul, D Avery, H K Dam, Truyen TranTruyen Tran, A Ghose
Stack Overflow is a highly successful Community Question Answering (CQA) service for software developers with more than three millions users and more than ten thousand posts per day. The large volume of questions makes it difficult for users to find questions that they are interested in answering. In this paper, we propose a number of approaches to predict who will answer a new question using the characteristics of the question (i.e. Topic) and users (i.e. Reputation), and the social network of Stack Overflow users (i.e. Interested in the same topic). Specifically, our approach aims to identify a group of users (candidates) who have the potential to answer a new question by using feature-based prediction approach and social network based prediction approach. We develop predictive models to predict whether an identified candidate answers a new question. This prediction helps motivate the knowledge exchanging in the community by routing relevant questions to potential answerers. The evaluation results demonstrate the effectiveness of our predictive models, achieving 44% precision, 59% recall, and 49% F-measure (average across all test sets). In addition, our candidate identification techniques can identify the answerers who actually answer questions up to 12.8% (average across all test sets).

History

Event

Australasian Software Engineering. Conference (24th : 2015 : Adelaide, South Australia)

Pagination

155 - 164

Publisher

IEEE

Location

Adelaide, South Australia

Place of publication

Piscataway, N.J.

Start date

2015-09-28

End date

2015-10-01

ISSN

1530-0803

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2015, IEEE

Title of proceedings

ASWEC 2015 : Proceedings of the 24th Australasian Software Engineering Conference

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