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This paper explores the application of quantum-inspired optimization algorithms in the training of large-scale Graph Neural Networks (GNNs) within distributed cloud-edge environments. GNNs have gained significant attention due to their ability to model complex relationships in graph-structured data, yet their training presents challenges such as high computational demand, inefficient resource allocation, and slow convergence, especially for large datasets. Traditional meta-heuristic algorithms, while useful, often face scalability and performance issues when applied to such large-scale tasks. To address these challenges, we propose a quantum-inspired meta-heuristic algorithm that leverages quantum principles, such as superposition and entanglement, to enhance optimization processes. The algorithm was integrated into a hybrid cloud-edge system, where computational tasks are dynamically distributed between edge nodes and the cloud, optimizing resource utilization and reducing latency. Our experimental results demonstrate significant improvements in training speed, resource efficiency, and convergence rate when compared to traditional optimization methods such as Genetic Algorithms and Simulated Annealing. The quantum-inspired algorithm not only accelerates the training process but also reduces memory usage, making it well-suited for large-scale GNN applications. Furthermore, the system's scalability was enhanced by the hybrid cloud-edge architecture, which balances computational load and enables real-time data processing. The findings suggest that quantum-inspired optimization algorithms can significantly improve the training of GNNs in distributed systems, opening new avenues for real-time applications in areas such as social network analysis, anomaly detection, and recommendation systems. Future work will focus on refining these algorithms to handle even larger datasets and more complex GNN architectures, with potential integration into edge devices for enhanced real-time decision-making.

Twitter is a social media that provides information for its users. Interactions on Twitter may increase the amount of data from its users. Business development cannot be separated from product competition between business actors. One way for companies to win the competition is to know the purchasing power of customers. A product's selling power can be known one way or another through user interaction on Twitter. User-generated content (UGC) results from data on Twitter. UGC data can be used to determine the product supply scheme taken by laptop products in this study. The method used to analyze the interaction is Social Network Analysis (SNA) by comparing the properties of the network. Social network modeling on UGC data was carried out on three laptops: Lenovo v14, Asus ZenBook S, and Acer Swift 3. From the graph visualization, it was found that Acer excels in two properties, namely "Size" and "Average Degree." Meanwhile, the Asus ZenBook S dominates the "Modularity" property.

The implementation of the 2020 Pilkada in Gunungpati District as a whole has improved in terms of the quality of its implementation. This is the result of the cooperation of all competent parties at the sub-district and village levels. This study aims to analyze the collaboration of the Supervisory Committee for the Election of Governors and Deputy Governors in 2020, Gunungpati District and to understand in depth the flow of information using Social Network Analysis (SNA). The results showed that the overall density of the supervisory committee network was 0.53 or 53%, so the characteristics of the network of members of the Panwaslu Kec.Gunungpati network were in the high category. Panwaslu members with the initials DAP, RV, WPU and M are the most dominant members of the Panwaslu with values of Centrality, Closeness and Betweness Centrality in the network.  

Diamond Printing is one of the largest offset printing companies with 32 years of experience and is located in the city of Surabaya, East Java. Data from HRD managers explained that there was no report from observations related to employee work effectiveness in terms of coordination and synergy between employees as seen from the communication and collaboration relationships. The absence of data related to the effectiveness of the performance of CV employees. Diamond Printing in terms of communication network mapping is one of the obstacles faced by HRD in determining KPI (key performance indicator). By using the Social Network Analysis (SNA) method with the help of UCINET 6 software, it is hoped that some employees will have advantages, especially in collaboration and communication in group network structures. There are three parameters used in SNA, including: degree centrality, closeness centrality, and betweenness centrality. This study involved 104 respondents (the entire population) with a sampling technique using snowball sampling and a questionnaire as a means of collecting data. The results of this study indicate that most of the collaboration and communication network interactions are dominated by manager level employees and department heads. Based on these findings, an innovation is needed from all stakeholders from CV. Diamond Printing in developing effective communication methods between its members.