Finding topical experts in question & answer communities

Thiago B. Procaci, Bernardo Pereira Nunes, Terhi Nurmikko-Fuller, Sean W.M. Siqueira

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Citations (Scopus)

Abstract

Question and Answer (Q&A) communities (such as Stackoverflow) have become important places for information exchange and knowledge creation. Their success relies predominantly on two aspects of the feedback generated by their members: quality and speed. Of these, the former reflects on the reputation of the community, whilst the latter is indicative of the efficiency of the Q&A system to correctly answer a given question. In this paper, we present a three phase study for identifying and recommending topical experts in Q&A communities. The first phase investigates the most relevant criteria for identifying reputable members of the community (often experts in a given field); the second phase introduces an approach based on semantic annotations to ascertain their area of specialism; and the last phase presents a method to recommend experts to answer questions in their areas of expertise. Our evaluation (carried out using realworld data from the Biology Stack Exchange Q&A community) shows that the numbers of answers provided by each member can be used as reliable indicators of expertise, and semantic annotations can be successfully used to identify the topics in which they specialize. Furthermore, on average, 74% of the recommendations suggested by our method were successful.

Original languageEnglish
Title of host publicationProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016
EditorsJ. Michael Spector, Chin-Chung Tsai, Ronghuai Huang, Paul Resta, Demetrios G Sampson, Kinshuk, Nian-Shing Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages407-411
Number of pages5
ISBN (Electronic)9781467390415
DOIs
Publication statusPublished - 28 Nov 2016
Externally publishedYes
Event16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016 - Austin, United States
Duration: 25 Jul 201628 Jul 2016

Publication series

NameProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016

Conference

Conference16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016
Country/TerritoryUnited States
CityAustin
Period25/07/1628/07/16

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