کنفرانس مهندسی برق ایران

صفحه اصلی / سی و یکمین کنفرانس بین المللی مهندسی برق

On the selection of superspreaders for advertising in science education using a new similarity measure

نویسندگان :

Sanaz Afsharian¹ Mohsen Heidari² Heidar Nosratzadeh³ Mojgan Khalifeh⁴

1- Islamic Azad University, Damavand Branch Tehran, Iran 2- Esfarayen University 3- Islamic Azad University, Damavand Branch 4- Science and Research Branch, Islamic Azad Univversity

کلمات کلیدی :

Ability of spread،Independent cascade model،Similarity; Superspreaders

چکیده :

Social networks play a very important role in solving the challenges of the contemporary world, including education, advertising, etc., many institutions use social network platforms to better promote educational courses, and for this reason, advertising is optimized in social network diffusion. Finding k superspreaders that have the greatest effect of publication and advertisement is one of the most important and challenging topics in the world of science. This issue has been the focus of many researchers due to its popularity and its connection with marketing science. But the algorithms presented in this problem face two challenges: the solution is not close to the real-world problems and the runtime. Also, in the algorithms presented in recent years, similarity in diffusion is ignored, which can play a very decisive role in information diffusion. Accordingly, to deal with these challenges, in this article, the NSPS algorithm is presented, which first calculates a new criterion based on centrality for similarity, the similarity criterion can create a large cascade of diffusion in social networks because nodes that are very similar to each other they can easily influence each other. It also uses network topology criteria to select seed nodes to estimate diffusion and reduce computational overhead. Finally, this algorithm is compared with the algorithm presented in recent years, which provides NSPS Influence spread algorithm and better runtime.

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