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Tools for Analytics and Cognition Framework for a Car-Sharing Use Case

Authors: Karadimce, Aleksandar; Capeska Bogatinoska, Dijana; Sefidanoski, Mirsat; Paunkoska Dimoska, Natasa; Marina, Ninoslav;

Tools for Analytics and Cognition Framework for a Car-Sharing Use Case

Abstract

Abstract The development of tools that can improve efficiency and inject intelligent insights into operational and mission-critical social media businesses through guided analytics is crucial for consumers, prosumers, and business markets. These tools will provide contextualised socially aware and spatial-temporal data aggregation, knowledge extraction, cognitive learning about users` behaviour, and risk quantification for the car-sharing use case. The proposed Tools for Analytics and Cognition (TAC) framework will provide a tool-set of guided analytics software for smart aggregation, cognition and interactive visualisation with a monitoring dashboard for the car-sharing use cases. The proposed TAC framework uses the dashboard to visually analyse the behaviour and engagement of the social media actors, diagnose performance risks and provide guided analytics to consumer prosumers and application providers to improve collaboration and revenues, using the established car-sharing qualitative mapping model. This framework has supplied a seamless coupling with distributed blockchain-based services for early alert, real-time tracking and updated data triggers for reach and engagement analysis of car-sharing events. Moreover, the TAC framework will allow car-sharing providers to analyse, control and track their investment to enhance monetary inclusion in the collaborative social media ecosystem.

Keywords

Guided Analytics, Data Aggregation, car-sharing, Augmented Cognitive, Microservices, Social Media

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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