Dynamic force-directed graph with weighted nodes for scholar network visualization
Through the growth of portals and venues to publish academic publications, the number of academic publications is growing exponentially in recent years. An effective exploration and fast navigation in the collection of academic publications become an urgent need to help academic researchers find pub...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
The Science and Information (SAI) Organization Limited
2022
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| Online Access: | http://psasir.upm.edu.my/id/eprint/101024/ https://thesai.org/Publications/ViewPaper?Volume=13&Issue=12&Code=IJACSA&SerialNo=89 |
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| Summary: | Through the growth of portals and venues to publish academic publications, the number of academic publications is growing exponentially in recent years. An effective exploration and fast navigation in the collection of academic publications become an urgent need to help academic researchers find publications related to their research and the surrounding community. A scholar network visualization approach is proposed to help users to explore a large number of academic publications concerning the strength of the relationship between each publication. The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. The proposed approach visualizes data by incorporating a force-directed graph with weighted nodes and vertices to give more descriptive information of millions of raw data such as author names, publication title, publication year, publication venue and number of citations from the scholar network dataset. By introducing a weighted relationship in the network visualization, the proposed approach can give a more insightful detail of each publication such as a highly cited publication by looking at and exploring the generated interactive graph. The proposal is targeted to be incorporated into a larger-scale scholar network analytical dashboard that can offer various visualization approaches under one flagship application. |
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