- Author
- Year
- 2015
- Title
- Early detection of topical expertise in community question and answering
- Event
- SIGIR 2015: 38th international ACM SIGIR conference on Research and development in information retrieval
- Book/source title
- SIGIR 2015
- Book/source subtitle
- proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 9-13, 2015, Santiago, Chile
- Pages (from-to)
- 995-998
- Publisher
- New York, NY: Association for Computing Machinery
- ISBN
- 9781450336215
- Document type
- Conference contribution
- Faculty
- Faculty of Science (FNWI)
- Institute
- Informatics Institute (IVI)
- Abstract
-
We focus on detecting potential topical experts in community question answering platforms early on in their lifecycle. We use a semi-supervised machine learning approach. We extract three types of feature: (i) textual, (ii) behavioral, and (iii) time-aware, which we use to predict whether a user will become an expert in the longterm. We compare our method to a machine learning method based on a state-of-the-art method in expertise retrieval. Results on data from Stack Overflow demonstrate the utility of adding behavioral and time-aware features to the baseline method with a net improvement in accuracy of 26% for very early detection of expertise.
- URL
- go to publisher's site
- Language
- English
- Persistent Identifier
- https://hdl.handle.net/11245/1.473954
Disclaimer/Complaints regulations
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library, or send a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.