Leveraging the network information for evaluating answer quality in a collaborative question answering portal

Chen, Lin & Nayak, Richi (2012) Leveraging the network information for evaluating answer quality in a collaborative question answering portal. Social Network Analysis and Mining, 2(3), pp. 197-215.

[img] Accepted Version (PDF 305kB)
Administrators only | Request a copy from author

View at publisher


Collaborative question answering (cQA) portals such as Yahoo! Answers allow users as askers or answer authors to communicate, and exchange information through the asking and answering of questions in the network. In their current set-up, answers to a question are arranged in chronological order. For effective information retrieval, it will be advantageous to have the users’ answers ranked according to their quality. This paper proposes a novel approach of evaluating and ranking the users’answers and recommending the top-n quality answers to information seekers. The proposed approach is based on a user-reputation method which assigns a score to an answer reflecting its answer author’s reputation level in the network. The proposed approach is evaluated on a dataset collected from a live cQA, namely, Yahoo! Answers. To compare the results obtained by the non-content-based user-reputation method, experiments were also conducted with several content-based methods that assign a score to an answer reflecting its content quality. Various combinations of non-content and content-based scores were also used in comparing results. Empirical analysis shows that the proposed method is able to rank the users’ answers and recommend the top-n answers with good accuracy. Results of the proposed method outperform the content-based methods, various combinations, and the results obtained by the popular link analysis method, HITS.

Impact and interest:

6 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 48198
Item Type: Journal Article
Refereed: Yes
Keywords: social network analysis, collaborative question answering portal, non-content method, content method
DOI: 10.1007/s13278-011-0046-4
ISSN: 1869-5450
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DATA FORMAT (080400)
Divisions: Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2012 Please consult the authors.
Copyright Statement: The original publication is available at SpringerLink http://www.springerlink.com
Deposited On: 24 Jan 2012 00:18
Last Modified: 26 Feb 2013 20:59

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page