How Hypergraph-to-Graph Conversion Affects Cooperative Working Visualization: A Multi-metric Evaluation

It is commonplace to use hypergraphs to represent cooperative work since hypergraphs explicitly capture complex interactions and connections, enabling researchers to analyze with ease. Nonetheless, hypergraphs are usually chaotic due to sophisticated relations between vertices. Therefore, it is necessary to look into which method prevails over other methods in specific circumstances. In our study, we propose an appraisal framework in which we use six quantitative and five qualitative metrics to assess the performance of each conversion method in terms of layout quality and effectiveness. The results show that while no method is ideal for all situations, certain methods, such as Centroid-single, perform well. Researchers can use our experiment results to select the optimal method tailored to their specific dataset and circumstances. This paper serves researchers and practitioners in choosing the most suitable conversion method for their research.