ارائه روشی برای یافتن عامل های پرنفوذ در انتشار اطلاعات در شبکه های اجتماعی مبتنی بر نظریه آنتروپی

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشگاه جامع امام حسین(ع)

چکیده

در حملات شناختی سایبری موضوع تحلیل انتشار اطلاعات در شبکه‌های اجتماعی برخط بسیار حائز اهمیت است که یکی از شاخه-های اصلی در تحلیل انتشار اطلاعات یافتن عامل‌های پرنفوذ می‌باشد. در بازاریابی ویروسی نیز تحت عنوان یافتن موثرترین عامل‌ها مطرح می‌شود. در این مقاله ضمن معرفی و محاسبه دو نوع عامل‌ پر اهمیت در انتشار اطلاعات (عامل‌های مرجع و فعال)، روشی برای یافتن این دودسته عامل‌های پراهمیت در انتشار اطلاعات در شبکه‌های اجتماعی برخط مبتنی بر نظریه آنتروپی ارائه و پیاده‌سازی شده است. روش پیشنهادی در این مقاله مبتنی است بر ارزیابی آنتروپی گراف شبکه اجتماعی برخط حاصل از انتشار اطلاعات با حذف مجموعه پرتاثیرترین عامل‌ها که بر اساس معیار درجه گره و معیار آنتروپی گره اندازه‌گیری شده است. آزمایش‌های این مقاله نشان می‌دهد که الگوریتم پیشنهادی نسبت به روش‌های قبلی، توانایی بیشتری در شناسایی مجموعه گره‌های پرنفوذ دارد، به‌طوری‌که مجموعه باقیمانده گره‌ها از همگنی قابل تنظیمی در معیار نفوذ برخوردار می‌شوند و همچنین معیاری را جهت مشخص نمودن تعداد گره‌های شاخص ارائه می‌کند.

تازه های تحقیق

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کلیدواژه‌ها


عنوان مقاله [English]

Introduction of the Entropy-Based Method for Finding Influential Nodes in Information Dissemination on Online Social Networks

نویسندگان [English]

  • Majid Ghayoori Sales
  • Gholamreza Bazdar
  • Abolfazl Sarkardeh
چکیده [English]

A complete reverse engineering (or blind identification) in an electronic battlefield determines the information conveyed by a received signal. Most of the research in the field of blind signal identification is around one-way and non-network communications in which the goal is to determine the information transmitted by a single transmitter. The first step of signal identification in communications networks is to determine the number of active users. In this paper, estimation of the number of users in a time-division multiple access (TDMA) network is considered. In order to estimate the number of users, a physical layer analysis can be applied to the received electromagnetic signals. However, due to some difficulties such as hardware limitations or closeness of active users, this method cannot always be employed. In these situations, a solution is to analyze the information in the upper layers of the network. In this paper, a method is proposed to estimate the number of active users using the redundant data generated by adaptive channel coding. Simulation results show that the proposed method is quite resistant against channel errors. In fact, the accuracy of the proposed method for signal to noise ratio of 7.3 dB is around 80%.

کلیدواژه‌ها [English]

  • Blind Estimation Of Number Of Users
  • TDMA Networks
  • Adaptive Channel Coding
  • Machine Learning

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