Analysis of the reputation system and user contributions on a question answering website: StackOverflow
Abstract
Question answering (Q&A) communities have been gaining popularity in the past few years. The success of such sites depends mainly on the contribution of a small number of expert users who provide a significant portion of the helpful answers, and so identifying users that have the potential of becoming strong contributers is an important task for owners of such communities.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Cites
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Flagged first, then by citations
Cited by
Sorted by citations
He, H., Yang, H., Burckhardt, P., Kapravelos, A., Vasilescu, B., & Kästner, C. (2026) · Proceedings of the 2026 IEEE/ACM 48th International Conference on Software Engineering · doi:10.1145/3744916.3764531 · Cited by 2 · see citing works
- Authors
- Movshovitz-Attias, D., Movshovitz-Attias, Y., Steenkiste, P., & Faloutsos, C.
- Affiliations
- Carnegie Mellon University, Pittsburgh, PA
- Carnegie Mellon University (US)
- Venue
- Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
- Publisher
- ACM
- Published
- 2013-08-25
- Pages
- 886-893
- OpenAlex
- W1981552292
- Cited by
- 141
- References
- 29
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 10 · 2023: 7 · 2022: 4 · 2021: 16 · 2020: 11 · 2019: 16 · 2018: 24 · 2017: 18 · 2016: 15 · 2015: 10 · 2014: 3
- FWCI
- 7.50
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Expert finding and Q&A systems
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Communication › Knowledge Management and Sharing
- Keywords
- reputation systems, user contribution, expert users, user identification, online communities, Q&A platforms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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