مقاله انگلیسی رایگان در مورد نحوه بهینه سازی تأثیر شبکه های اجتماعی – ۲۰۱۹ IEEE

IEEE

 

مشخصات مقاله
ترجمه عنوان مقاله نحوه بهینه سازی تأثیر شبکه های اجتماعی
عنوان انگلیسی مقاله How to Optimize Social Network Influence
انتشار مقاله سال ۲۰۱۹
تعداد صفحات مقاله انگلیسی ۴ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه IEEE
مقاله بیس این مقاله بیس نمیباشد
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
مدل مفهومی ندارد
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط مهندسی فناوری اطلاعات
گرایش های مرتبط اینترنت و شبکه های گسترده، مدیریت سیستم های اطلاعات، شبکه های کامپیوتری
نوع ارائه مقاله
کنفرانس
کنفرانس دومین کنفرانس بین المللی هوش مصنوعی و مهندسی دانش – Second International Conference on Artificial Intelligence and Knowledge Engineering
کلمات کلیدی بهینه سازی نفوذ، تشخیص تشکل، داده های بزرگ
کلمات کلیدی انگلیسی Influence Optimization، Community Detection، Big Data
شناسه دیجیتال – doi
https://doi.org/10.1109/AIKE.2019.00029
کد محصول E13160
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فهرست مطالب مقاله:
Abstract

I- Introduction

II- Related Work

III- Proposed Appraoch

IV- Conclusion

References

 

بخشی از متن مقاله:

Abstract

Online social networks are rapidly becoming an identifying feature of modern society. As online communities continue to grow, business networks of different domains also grow. As online social network begins to become increasingly integrated in our daily lives, the optimization of social network influence becomes increasingly important. In this paper, I propose to optimize influence using a modified linear threshold model. Under this model, I will focus on strategically selecting a set of users that will optimize our influence within the network. I call this type of problem as influence optimization. In this paper, I will propose a model to optimize social network influence.

INTRODUCTION

With the rapid expansion of online social networks, online social networks have become a critical medium of communication and interactions between individuals. Online social networks have provided ways to communicate strangers and friends alike. With online social networks, communication is faster than ever, and the scope of communication is much more diverse. Due to the implications of social networks, it has become necessary for companies and researchers to study and gain understanding of them. In particular, it has become very beneficial for researchers to study the diffusion of information within an online social network. While online social networks retain many properties of a regular networks such as local influence, online social networks have allowed to expand influence beyond that of the local network. Ultimately, online social networks have expanded individual scopes of influence. An important topic for online social networks is influence maximization. The objective of influence maximization is to maximize the number of individuals involved with a single idea within a network, which can range from news, gossip, and products, to recommendations and etc. This problem within networks has various applications such as marketing, advertising, and even the medical field. For example, a company might want to promote a new product and needs to select a set of users that can maximize the exposure of the advertised product. By selecting an optimal set of users, a company can maximize its profits and minimize its losses. Some popular influence diffusion models include the independent cascade (IC) and the linear threshold (LT). Both models are used to characterize how influence propagates throughout the network starting from the initial seed nodes. In this paper, I will use a propagation model that will have characteristics of both.

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