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 ๐ AINA Workshops
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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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