این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
Journal of Industrial and Systems Engineering، جلد ۱۳، شماره ۳، صفحات ۱۶-۴۰

عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله

عنوان انگلیسی Influence maximization in complex social networks based on community structure
چکیده انگلیسی مقاله Many real-world networks, including biological networks, internet, information and social networks can be modeled by a complex network consisting of a large number of elements connected to each other. One of the important issues in complex networks is the evaluation of node importance because of its wide usage and great theoretical significance, such as in information diffusion, control of disease spreading, viral marketing and rumor dynamics. A fundamental issue is to identify a set of most influential individuals who would maximize the influence spread of the network. In this paper, we propose a novel algorithm for identifying influential nodes in complex networks with community structure without having to determine the number of seed nodes based on genetic algorithm. The proposed algorithm can identify influential nodes with three methods at each stage (degree centrality, random and structural hole) in each community and measure the spread of influence again at each stage. This process continues until the end of the genetic algorithm, and at the last stage, the most influential nodes are identified with maximum diffusion in each community. Our community-based influencers detection approach enables us to find more influential nodes than those suggested by page-rank and other centrality measures. Furthermore, the proposed algorithm does not require determining the number of k initial active nodes.
کلیدواژه‌های انگلیسی مقاله Influential nodes,Complex networks,community detection,influence maximization

نویسندگان مقاله Babak Amiri |
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Mohammad Fathian |
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Elnaz Asaadi |
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran


نشانی اینترنتی https://www.jise.ir/article_128461_a5fb2d5a6affa0c9637da437d643ba6d.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات