Binesh, Neda, Ghatee, Mehdi. (1401). Using principal eigenvectors of Laplacian-Plus matrix to identify spreaders of social networks under linear threshold diffusion model. نشریه مهندسی عمران امیرکبیر, 3(2), 153-164. doi: 10.22060/ajmc.2022.20727.1074
Neda Binesh; Mehdi Ghatee. "Using principal eigenvectors of Laplacian-Plus matrix to identify spreaders of social networks under linear threshold diffusion model". نشریه مهندسی عمران امیرکبیر, 3, 2, 1401, 153-164. doi: 10.22060/ajmc.2022.20727.1074
Binesh, Neda, Ghatee, Mehdi. (1401). 'Using principal eigenvectors of Laplacian-Plus matrix to identify spreaders of social networks under linear threshold diffusion model', نشریه مهندسی عمران امیرکبیر, 3(2), pp. 153-164. doi: 10.22060/ajmc.2022.20727.1074
Binesh, Neda, Ghatee, Mehdi. Using principal eigenvectors of Laplacian-Plus matrix to identify spreaders of social networks under linear threshold diffusion model. نشریه مهندسی عمران امیرکبیر, 1401; 3(2): 153-164. doi: 10.22060/ajmc.2022.20727.1074

Using principal eigenvectors of Laplacian-Plus matrix to identify spreaders of social networks under linear threshold diffusion model

AUT Journal of Mathematics and Computing
مقاله 4، دوره 3، شماره 2، آذر 2022، صفحه 153-164    اصل مقاله (949.29 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22060/ajmc.2022.20727.1074
نویسندگان
Neda Binesh؛ Mehdi Ghatee*
Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
چکیده
Influence maximization (IM) is a challenging problem in social networks to identify initial spreaders with the best influence on other nodes. It is a need to solve this problem with the minimum diffusion time and the most coverage on the communities. However, the spreaders are rarely dependent on diffusion models. A recent research [N. Binesh, M. Ghatee, Distance-Aware Optimization Model for Influential Nodes Identification in Social Networks with Independent Cascade Diffusion, Information Sciences, 581 (2021) 88-105] proposed DASF algorithm for spreaders selection by the Independent Cascade (IC) diffusion model. Here, we present a new optimization model to find spreaders under Linear Threshold (LT) diffusion model. LT is one of the most important models to imitate the behavior of influence propagation in social networks. Our model is a quadratic programming problem based on LaplacianPlus matrix. We derive its solution by some principal eigenvectors of Laplacian-Plus matrix. We organize the solution process as DALT algorithm. Without community detection, it can identify the spreaders with maximum inter-communities distance, minimum intra-communities distance, and the most significant degrees. By considering various well-known social networks, we show that DALT provides brilliant results and overcomes other local and global spreader finders, especially in social networks with community structures.
کلیدواژه‌ها
Social networks؛ Influence maximization؛ Linear threshold model؛ Laplacian-Plus matrix؛ Eigenvectors
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