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But most geographic analyses of geotagged social media data have failed to mobilize a sufficiently complex understanding of socio-spatial relations.
More importantly, quality aspects of social media data have been analysed mainly with supervised machine learning.
Studies on emergency response using social media data have drawn much academic attention.
All of these social media data have been automatically harvested by KEF.
Social media data have been gaining increasing attention in studies of emergencies and disasters, a field often referred to as crisis informatics[53].
As a consequence, tasks related to the analysis of historical news events based on social media data have not been explored, which limits any type of comparative historical research, causality analysis, and discovery of knowledge from patterns extracted from aggregated social media event information.
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We know that the social media data has the capability to reach with more efficacy.
Social media data has provided various insights into the behaviour of consumers and businesses.
However, reference architecture (RA) design for data quality management in social media data has only been addressed recently [11].
Particularly, reference architecture for quality management in social media data has been extended and evaluated based on the implementation architecture.
How can firms use social media when discussing specific stocks with clients? A. Social media data has become more relevant.
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