A Topic Sensitive SimRank (TSSR) model for experts finding on online research social platforms

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Author(s)

  • Wenping Zhang
  • Wei Du
  • Wei Xu
  • Shengtao Tang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationPacific Asia Conference on Information Systems, PACIS 2016 - Proceedings
PublisherPacific Asia Conference on Information Systems
ISBN (Print)9789860491029
Publication statusPublished - 2016

Conference

Title20th Pacific Asia Conference on Information Systems (PACIS 2016)
LocationNice Prince Hotel
PlaceTaiwan
CityChiayi
Period27 June - 1 July 2016

Abstract

As an efficient online academic information repository and information channel with crowds' contribution, online research social platforms have become an efficient tool for various kinds of research & management applications. Social network platforms have also become a major source to seek for field experts. They have advantages of crowd contributions, easy to access without geographic restrictions and avoiding conflict of interests over traditional database and search engine based approaches. However, current research attempts to find experts based on features such as published research work, social relationships, and online behaviours (e.g. reads and downloads of publications) on social platforms, they ignore to verify the reliability of identified experts. To bridge this gap, this research proposes an innovative Topic Sensitive SimRank (TSSR) model to identify "real" experts on social network platforms. TSSR model includes three components: LDA for Expertise Extension, Topic Sensitive Network for Reputation Measurement, and Topic Sensitive SimRank for unsuitable experts detection. We also design a parallel computing strategy to improve the efficiency of the proposed methods. Last, to verify the effectiveness of the proposed model, we design an experiment on one of the research social platforms-ScholarMate to seek for experts for companies that need academic-industry collaboration.

Research Area(s)

  • Experts finding, Social network analysis, Social platform, Topic Sensitive SimRank

Citation Format(s)

A Topic Sensitive SimRank (TSSR) model for experts finding on online research social platforms. / Zhang, Wenping; Ye, Liying; Du, Wei; Ma, Jian; Xu, Wei; Tang, Shengtao.

Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings. Pacific Asia Conference on Information Systems, 2016.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review