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Academic Collaboration Recommendation for Computer Science Researchers Using Social Network Analysis

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Abstract

In order to improve the quality and quantity of the performance in computing in Nigeria Universities, there is need for a functioning research networking application through which they can exchange ideas. This is because academics tend to be more comfortable communicating with each other, asking questions and more importantly, such networking will provide mentorship in the Nigeria academic community. In order to make for this, several recommendations have been suggested but not scientific. Therefore to bridge this gap, this paper examines the properties of co-authorship network in Covenant University, Computer Science department. Properties of network such as centrality measures, network coefficient and so on are discovered. A collaboration recommendation application is then developed using the link prediction based on the Adamic-Adar Index measure. In conclusion, the result gotten from the network analysis is a valuable source of information for accessing the different centrality values of researchers in computer science. It also formed the foundation for developing an academic collaboration recommendation system for a small world research network. This will therefore improve the quantity and quality of performance of computer science academics in Nigeria.

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Data Availability

The data used for the research is available on request.

Code Availability

The code for analysing the data is available on request.

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Funding

The authors appreciate Covenant University for sponsoring the publication of this article.

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Authors and Affiliations

  1. Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Ibukun T. Afolabi & Atinuke Ayo

  2. Department of Mathematics, Covenant University, Ota, Nigeria

    Oluwole A. Odetunmibi

Authors
  1. Ibukun T. Afolabi
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  2. Atinuke Ayo
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  3. Oluwole A. Odetunmibi
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Correspondence to Oluwole A. Odetunmibi.

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Afolabi, I.T., Ayo, A. & Odetunmibi, O.A. Academic Collaboration Recommendation for Computer Science Researchers Using Social Network Analysis. Wireless Pers Commun 121, 487–501 (2021). https://doi.org/10.1007/s11277-021-08646-2

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