The purpose of this study is data generated from any social networking sites may provide some hidden knowledge on a particular domain. Based on this concept the previous paper had proved that social connectivity enhancement takes place through triadic closure and embeddedness in terms of social network graph-theoretic approach. Further, the work was justified by genetic algorithm (GA) where observation showed how interdisciplinary work can occur because of crossover, and therefore, different groups of researchers could be identified. Further enhancement of the work has been focused on in this paper.
In continuation with the previous work, this paper detects other possible fields related to “high graded researchers” who can share the information with the other group of researchers (“imminent high graded” and “new researchers”) using particle swarm optimization (PSO) technique.
While exploitation was done using GA in the previous work, exploration is done in the current work based on PSO using the same grade score value to the objective function. Both the velocity and direction of high graded researchers in this extended work could be derived, which was not possible using GA.
This could help the next two levels of researchers (“imminent high graded researchers” and “new researchers”) in expanding their research fields in line with the fields of high graded researchers.
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