Handling Publication Imbalance for Effective Community Detection in Scholarly Networks
type: article
type: FAIRDigitalObject
creator: https://orcid.org/0000-0001-8726-8226
creator: https://orcid.org/0000-0001-9487-5622
creator: https://orcid.org/0000-0002-3588-6257
publisher: 01xsmwp79
subject: topic 3316
comment: Finding potential research collaborators is a challenging task, especially in today’s fast-growing, interdisciplinary research landscape. While traditional methods rely on observable ties like co-authorships and citations, we focus solely on publication content to build a topic-based research network using BERTopic with a fine-tuned SciBERT model that connects and recommends researchers across disciplines based on shared topical interests. A key challenge we address is publication imbalance, where some researchers publish much more than others, often across several topics. Without careful handling, their less frequent interests are hidden under dominant topics, limiting the network’s ability to capture their full research scope. To tackle this, we introduce a cloning strategy that clusters a researcher’s publications and treats each cluster as a separate node. This allows researchers to belong to multiple communities, improving the detection of interdisciplinary links. Evaluation shows that the cloned network leads to more meaningful communities and uncovers broader collaboration opportunities.
funder: 021nxhr62
end date: Feburary 3 2026
start date: 2024

https://w3id.org/np/RAoA342WhOZaebSPn8b0n9Yjn4yZfcb3Lb1JYD9hLpaf0
created: 2026-06-10T23:15:00.829Z
creator: Emily Regalado
license: https://creativecommons.org/licenses/by/4.0/
introduces: Handling Publication Imbalance for Effective Community Detection in Scholarly Networks
was created at: nanodash.knowledgepixels.com
type: Nanopublication
has assertion: assertion
has provenance: provenance
has publication info: pubinfo

sig
has algorithm: RSA
signed by: Emily Regalado