Social Credibility Incorporating Semantic Analysis and Machine Learning: A Survey of the State-of-the-Art and Future Research Directions

  • Bilal Abu-SalihEmail author
  • Bushra Bremie
  • Pornpit Wongthongtham
  • Kevin Duan
  • Tomayess Issa
  • Kit Yan Chan
  • Mohammad Alhabashneh
  • Teshreen Albtoush
  • Sulaiman Alqahtani
  • Abdullah Alqahtani
  • Muteeb Alahmari
  • Naser Alshareef
  • Abdulaziz Albahlal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 927)


The wealth of Social Big Data (SBD) represents a unique opportunity for organisations to obtain the excessive use of such data abundance to increase their revenues. Hence, there is an imperative need to capture, load, store, process, analyse, transform, interpret, and visualise such manifold social datasets to develop meaningful insights that are specific to an application’s domain. This paper lays the theoretical background by introducing the state-of-the-art literature review of the research topic. This is associated with a critical evaluation of the current approaches, and fortified with certain recommendations indicated to bridge the research gap.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bilal Abu-Salih
    • 1
    • 2
    Email author
  • Bushra Bremie
    • 1
  • Pornpit Wongthongtham
    • 1
  • Kevin Duan
    • 1
  • Tomayess Issa
    • 1
  • Kit Yan Chan
    • 1
  • Mohammad Alhabashneh
    • 1
  • Teshreen Albtoush
    • 1
  • Sulaiman Alqahtani
    • 1
  • Abdullah Alqahtani
    • 1
  • Muteeb Alahmari
    • 1
  • Naser Alshareef
    • 1
  • Abdulaziz Albahlal
    • 1
  1. 1.Curtin UniversityPerthAustralia
  2. 2.The University of JordanAmmanJordan

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