Academic Journal

GraphOptima: A graph layout optimization framework for visualizing large networks

التفاصيل البيبلوغرافية
العنوان: GraphOptima: A graph layout optimization framework for visualizing large networks
المؤلفون: Anatoliy Gruzd, Jingwei Zhang, Philip Mai
المصدر: SoftwareX, Vol 29, Iss , Pp 102034- (2025)
بيانات النشر: Elsevier, 2025.
سنة النشر: 2025
المجموعة: LCC:Computer software
مصطلحات موضوعية: Online networks, Social network analysis, Network science, Graph visualization, Layout optimization, Readability metrics, Computer software, QA76.75-76.765
الوصف: Graphs illustrating online networks, participants, and interactions have become essential tools for studying issues like misinformation, botnets, algorithmic filtering and many other areas of research. Researchers use these visual representations to examine underlying structures, form hypotheses, and share their findings. However, achieving visually appealing network visualizations often involves manually testing several layout algorithms and fine-tuning their parameters. Furthermore, due to the computational complexity of rendering large networks, there is also usually a long wait time between parameter tests. This paper introduces GraphOptima, a framework for optimizing graph layout and readability metrics. GraphOptima automates parameter selection, layout computation, and readability metric calculation. Rather than providing a single ‘optimal’ solution, the framework generates a range of solutions under different parameters, enabling researchers to explore multiple solutions based on multi-objective optimization. The framework supports parallel layout calculations without modifying the layout algorithm, efficiently managing computational resources in high-performance computing environments. In addition to introducing a new framework, the paper shows how GraphOptima can be used to explore distinct layouts for three sample networks and to decide on trade-offs among three readability metrics: crosslessness, normalized edge length variance, and min angle.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2352-7110
Relation: http://www.sciencedirect.com/science/article/pii/S2352711025000019; https://doaj.org/toc/2352-7110
DOI: 10.1016/j.softx.2025.102034
URL الوصول: https://doaj.org/article/9a1d5ab574a54e6386ca323ceecd0c5f
رقم الانضمام: edsdoj.9a1d5ab574a54e6386ca323ceecd0c5f
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:23527110
DOI:10.1016/j.softx.2025.102034