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

February 27, 2019 ยท The Cartographer ยท ๐Ÿ› AINA Workshops

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: Social Credibility Incorporating Semantic Analysis and Machine Learning: A Survey of the State-of-th"

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Authors Bilal Abu-Salih, 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 arXiv ID 1902.10402 Category cs.SI: Social & Info Networks Cross-listed cs.LG Citations 23 Venue AINA Workshops Last Checked 2 days ago
Abstract
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 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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