Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Српски
  • Yкраї́нська
  • Log In
    Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of Digital Repository
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Српски
  • Yкраї́нська
  • Log In
    Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "OUNICI et MECHIKI, Khaled et Djaber"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    ItemOpen Access
    Towards a new simplistic approach for influential web users identification in social networks
    (FACULTY: Mathematics and Computer Science DEPARTMENT: Computer Science - BRANCH: Computer Science OPTION: IDO, 2021) OUNICI et MECHIKI, Khaled et Djaber
    Social influence is the science of influence, persuasion, and compliance. It is the process of influencing the behavior of one person by another, it is the process by which individuals adapt their opinion, revise their beliefs, or change their behavior as a result of social interactions with other people. Nowadays, researchers in the Social Network Analysis (SNA) community are trying to figure out the factors that impact positively or negatively on the propagation of influence among the elements of a social graph. Our mission is to understand the diffusion process of influence and propose how it can be affected by the structural and behavioural aspects of social networks. Moreover, we will try to compare the proposed model with other models using real-world databases. The results revealed the effectiveness of the LTM and ICM models in analyzing the diffusion process in social networks.

All Rights Reserved - University of M'Sila - UMB Electronic Portal © 2024

  • Cookie settings
  • Privacy policy
  • Terms of Use