A new greedy method based on cascade model for the influence maximization problem in social networks.

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Bouyer Asgarali; Ahmadi bani Hamid

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY Year:2019 | Volume:10 | Issue:37-38 Page(s): 85-100

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

352

Download:

Cites:

Information Journal Paper

Title

A new greedy method based on cascade model for the influence maximization problem in social networks.

Author(s)

Bouyer Asgarali | Ahmadi bani Hamid | Issue Writer Certificate

Keywords

Independent cascade modelQ1

influence maximizationQ1

diffusionQ2

social networkQ2

Abstract

influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social networks that maximize the influential spreading. Recently, there is a quick growing in studying on and diffusion. In recent years, several algorithms have been proposed for influence maximization problem. These studies include viral marketing, spreading of rumors, innovation, spread of diseases, etc. In this paper we present a new method for solving the for influence maximization problem that is called ICIM-GREEDY algorithm. In the proposed algorithm, we consider two important criteria that are not considered in previous work, one is strength of influence and another is sensitivity to influence. The proposed method is evaluated on standard datasets. The results show that the proposed method compared to other comparable algorithms has a better quality in finding the 50 influential nodes (seeds). Furthermore, ICIM-GREEDY often has better time complexity than other compared algorithms due to relatively fast convergence.

Cites

No record.

References

No record.

Cite

APA: Copy

Bouyer, Asgarali, & Ahmadi bani, Hamid. (2019). A new greedy method based on cascade model for the influence maximization problem in social networks.. IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY, 10(37-38 ), 85-100. SID. https://sid.ir/paper/370184/en

Vancouver: Copy

Bouyer Asgarali, Ahmadi bani Hamid. A new greedy method based on cascade model for the influence maximization problem in social networks.. IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY[Internet]. 2019;10(37-38 ):85-100. Available from: https://sid.ir/paper/370184/en

IEEE: Copy

Asgarali Bouyer, and Hamid Ahmadi bani, “A new greedy method based on cascade model for the influence maximization problem in social networks.,” IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY, vol. 10, no. 37-38 , pp. 85–100, 2019, [Online]. Available: https://sid.ir/paper/370184/en

Related Journal Papers