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Detection of Leading Experts from ResearchGate

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  • Eya Ben Ahmed

    (Higher Institute of Applied Science and Technology of Sousse, Sousse, Tunisia)

Abstract

This article describes how thanks to the technological development, social media has propagated in recent years. The latter describes a range of Web-based platforms that enable people to socially interact with one another online. Several types of social media appeared. In this context, the author focuses on scientific social network which connects the researchers and allow them to communicate and collaborate online. In this paper, we, particularly, aim to detect the scientific leaders through firstly detect communities in social network then identify the leader of each group. To do this, the author introduces a new hierarchical semi-supervised clustering method based on ordinal density. The results of carried out experiments on real scientific warehouse have shown significant profits in terms of accuracy and performance.

Suggested Citation

  • Eya Ben Ahmed, 2018. "Detection of Leading Experts from ResearchGate," International Journal of Business Analytics (IJBAN), IGI Global, vol. 5(3), pages 67-86, July.
    • Handle: RePEc:igg:jban00:v:5:y:2018:i:3:p:67-86
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