Michael Zgurovsky, Andriy Boldak, Dmitry Lande, Kostiantyn Yefremov, Maria Perestyuk.
Predictive Online Analysis of Social Transformations based on the Assessment of Dissimilarities between Government Actions and Society's Expectations
// 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC) (Kyiv, 5-9 Oct. 2020). DOI: doi.org/10.1109/SAIC51296.2020.9239186, ISBN: 978-1-7281-9084-6
 

The methodology for assessing the effectiveness of social transformations has been developed, which is based on determining the degree of inconsistency between government actions and expectations of the society, and the synergy (social activity) of people, depending on the above-mentioned degree of inconsistency. A set of tools and services has been developed to quantify the parameters and characteristics of social transformations within the Advanced Analytics integrated online platform. These tools allow us to monitor open online publications and social networks on the basis of linguistic sentiment analysis of a large number of messages. The effectiveness of the proposed methodology, tools and services of the Advanced Analytics online platform was proved using the example of quantitative assessment of Ukraine.s population attitude to actions of the authorities related to the strengthening of quarantine measures aimed at counteracting the spread of the COVID-19 pandemic.
Keywords:
vector of government actions, vector of society.s expectations, vector of transformations (reforms), linguistic sentiment analysis of Internet media data and social networks, open source intelligence, Advanced Analytics online platform

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