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Tools for Analytics and Cognition for Crowd Journalism Application

Authors: N. Paunkoska Dimoska; A. Hristov; A. Karadimce; N. Marina; M. Sefidanoski;

Tools for Analytics and Cognition for Crowd Journalism Application

Abstract

Businesses and service consumers should take advantage of social media’s ability to adapt their marketing campaigns to achieve a long-term strategic advantage. Setting quantitative and attainable expectations is critical to the progress of every marketing or business endeavour. The development of tools for analytics and cognition (TAC) is essential for customers and providers to increase productivity and inject intelligent insights into operational and mission-critical social media businesses through driven analytics. In this paper, the developed tools provide guided analytics software for intelligent aggregation, cognition and interactive visualization with a monitoring dashboard for concrete crowd journalism use cases. The provider receives an approach to a guided analytic dashboard filled with meaningful business visualization predictions. Among the other things, he can inspect the quantitative metrics for a sharing economy and estimate stakeholders’ channel monetization as a new innovative quantified value by engaging users with trusted content. TAC uses this principle of engagement rate measurements and provides visualization insights for stakeholders to choose the right track for boosting their business.

Keywords

Social media, Crowd journalism, Sharing economy, Guided analytics, Engagement rate

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Impulse provided by BIP!
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OpenAIRE UsageCountsViews provided by UsageCounts
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