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Major findings: ScholarNodes, a web interface that successfully integrates partition-based (Louvain) and similarity-based (Spectral) community detection algorithms with the BM25 ranking algorithm to recommend interdisciplinary collaborations within academic social networks. By analyzing publication metadata from the OpenAlex dataset, the authors demonstrated that a topic-similarity network can effectively identify latent researcher communities and provide meaningful mentorship and grant-teaming recommendations that transcend traditional departmental boundaries.
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ScholarNodes: Applying Content-based Filtering to RecommendInterdisciplinary Communities within Scholarly Social Networks
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