QDEE: Question Difficulty and Expertise Estimation in Community Question Answering Sites
Jiankai Sun, Sobhan Moosavi, Rajiv Ramnath, Srinivasan, Parthasarathy

TL;DR
This paper introduces QDEE, a language-agnostic framework that estimates question difficulty and user expertise in community Q&A sites, improving question routing and understanding user roles.
Contribution
The paper's novelty lies in applying social agony to estimate question difficulty and user expertise, and in addressing the cold-start problem with textual features.
Findings
QDEE outperforms state-of-the-art models in real-world datasets.
It effectively estimates difficulty levels for new questions.
The framework characterizes user expertise and roles in CQAs.
Abstract
In this paper, we present a framework for Question Difficulty and Expertise Estimation (QDEE) in Community Question Answering sites (CQAs) such as Yahoo! Answers and Stack Overflow, which tackles a fundamental challenge in crowdsourcing: how to appropriately route and assign questions to users with the suitable expertise. This problem domain has been the subject of much research and includes both language-agnostic as well as language conscious solutions. We bring to bear a key language-agnostic insight: that users gain expertise and therefore tend to ask as well as answer more difficult questions over time. We use this insight within the popular competition (directed) graph model to estimate question difficulty and user expertise by identifying key hierarchical structure within said model. An important and novel contribution here is the application of "social agony" to this problem…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsExpert finding and Q&A systems · Topic Modeling · Recommender Systems and Techniques
