A deep adaptive social media framework using self-attention handling mixed messages monitoring unrest events

Communication is vital for us as the utmost element for decision making. The impact of mixed messages is very vital especially during critical moments, such as pandemic and cyber security situations. Mixed messages itself are contradictory, inconsistent, or unclear in its motive or intent. The densi...

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Bibliographic Details
Main Authors: Kamal, Bin Ramli Ramli Ahmad, Shafiq, Bin Abd Aziz Muhd Eizan, Juhaida, Binti Ismail, Aisyah, Binti Mat Jasin, Ikhwan, Bin Zolkefley Mohd Khairul
Format: Conference Proceeding
Language:English
Subjects:
Cybersecurity
Decision making
Digital media
Knowledge bases (artificial intelligence)
Messages
News
Social networks
Online Access:Get full text
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Summary:Communication is vital for us as the utmost element for decision making. The impact of mixed messages is very vital especially during critical moments, such as pandemic and cyber security situations. Mixed messages itself are contradictory, inconsistent, or unclear in its motive or intent. The densities of mixed messages decisions based on various news sources in social media cannot be overcome solely with non-adaptive approaches. Among Monitor Analyze Plan Execute (MAPE), Monitor Analyze Plane Execute Knowledge Base (MAPE-K) and No MAPE Concepts and primary studies consider the implementation of MAPE-K for addressing adaptation mechanism. The proposed research with the combination of self-attention, adaptive MAPE-K framework, and live running news mining is presented to address highlighted issues. These features identified the targeted, like the type of news and author names. The proposed research is expected to handle ongoing running news and adaptively developed the suggested feedback for mixed messages. The research seeks to assess the results from running news features. Mixed messages monitor, Self-attention and MAPE-K adaptive framework based on autonomic computing is explored. Modality Exploration and Extraction, Adaptive Framework, Experiment Evaluation are the sequence of methods adopted in this research. A vital contribution is the adaptive framework to monitor mixed messages and mitigate the unwanted perspective in any outbreak. The expected result once the thorough development of this proposal is to receive crystal clear mixed messages information and resulted in non-biased decision making.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0127736