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[PRE REVIEW]: HINA: A Learning Analytics Tool for Heterogenous Interaction Network Analysis in Python #7995
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Five most similar historical JOSS papers: repytah: An Open-Source Python Package for Building Aligned Hierarchies for Sequential Data visxhclust: An R Shiny package for visual exploration of hierarchical clustering XGI: A Python package for higher-order interaction networks sknet: A Python framework for Machine Learning in Complex Networks PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs |
We have moved the repository to this link https://github.com/orgs/SHF-NAILResearchGroup/repositories, please use the updated repository link for the review, thanks! Shihui Feng |
@editorialbot set https://github.com/SHF-NAILResearchGroup/HINA as repository |
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👋 @shihuife - the commit history of your repository seems to be fairly young. Can you discuss the development history of your software a bit here? |
Hi @crvernon, Thank you for the question :) Over the past few years, I have been working on developing novel network-based methods to analyze learning process data, resulting in two publications so far (Feng et al., 2024; Feng et al., 2025). Initially, the code was developed and analyzed locally without being uploaded to a public repository. However, since last year, as the three-level methods have matured, I began collaborating with my team to organize and prepare the repository for release. We recently moved the package to the new repository path under my research group, as I am in the process of creating a GitHub organisation to share other open-source methods developed by my research group in learning-related contexts. I hope this provides clarity on the development process. Let me know if you have any further questions! Feng, S., Yan, L., Zhao, L., Maldonado, R. M., & Gašević, D. (2024, March). Heterogenous network analytics of small group teamwork: Using multimodal data to uncover individual behavioral engagement strategies. In Proceedings of the 14th learning analytics and knowledge conference (pp. 587-597). Feng, S., Gibson, D., & Gašević, D. . (2025). Analyzing Students’ Emerging Roles Based on Quantity and Heterogeneity of Individual Contributions in Small Group Online Collaborative Learning Using Bipartite Network Analysis. Journal of Learning Analytics, 12(1), 253-270. https://doi.org/10.18608/jla.2025.8431 |
@editorialbot invite @vissarion as editor 👋 Do you have time to take this one on @vissarion? |
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@crvernon I already have three papers on my stack, I would take this one only if it is urgent. |
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Hi @drj11, @dataspider, and @etShaw-zh, would you be able to review this paper for JOSS? |
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Five most similar historical JOSS papers: repytah: An Open-Source Python Package for Building Aligned Hierarchies for Sequential Data visxhclust: An R Shiny package for visual exploration of hierarchical clustering sknet: A Python framework for Machine Learning in Complex Networks XGI: A Python package for higher-order interaction networks PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs |
Submitting author: @shihuife (shihui Feng)
Repository: https://github.com/SHF-NAILResearchGroup/HINA
Branch with paper.md (empty if default branch):
Version: 0.4.7
Editor: @juliaferraioli
Reviewers: @etShaw-zh
Managing EiC: Arfon Smith
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