Increasing the responsiveness of recommended expert collaborators for online open projects

Mohammad Y. Allaho, Wang Chien Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We consider the experts recommendation problem for open collaborative projects in large-scale Open Source Software (OSS) communities. In large-scale online community, recommending expert collaborators to a project coordinator or lead developer has two prominent challenges: (i) the "cold shoulder" problem, which is the lack of interest from the experts to collaborate and share their skills, and (ii) the "cold start" problem, which is an issue with community members who has scarce data history. In this paper, we consider the Degree of Knowledge (DoK) which imposes the knowledge of the skills factor, and the Social Relative Importance (SRI) which imposes the social distance factor to tackle the aforementioned challenges. We propose four DoK models and integrate them with three SRI methods under our proposed Expert Ranking (ER) framework to rank the candidate expert collaborators based on their likelihood of collaborating in response to a query formulated by the social network of a query initiator and certain required skills to a project/task. We evaluate our proposal using a dataset collected from Github.com, which is one of the most fast-growing, large-scale online OSS community. In addition, we test the models under different data scarcity levels. The experiment shows promising results of recommending expert collaborators who tend to make real collaborations to projects.

Original languageEnglish (US)
Title of host publicationCIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery, Inc
Pages749-758
Number of pages10
ISBN (Electronic)9781450325981
DOIs
StatePublished - Nov 3 2014
Event23rd ACM International Conference on Information and Knowledge Management, CIKM 2014 - Shanghai, China
Duration: Nov 3 2014Nov 7 2014

Publication series

NameCIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management

Other

Other23rd ACM International Conference on Information and Knowledge Management, CIKM 2014
CountryChina
CityShanghai
Period11/3/1411/7/14

All Science Journal Classification (ASJC) codes

  • Information Systems and Management
  • Computer Science Applications
  • Information Systems

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