Api-sociology and Google global community: the live system of social transformation
DOI:
https://doi.org/10.14515/monitoring.2019.2.03Keywords:
text analytics, Big Data, Google, visualization, Data Mining, API-sociology, drug addiction, cluster analysisAbstract
In this paper, the authors present the results of morphological text big data analysis for the occurrence of keywords over the Internet for different countries. The values for the words were requested from the databases of the Google search engine via API-access using special software created at the Vladivostok State University of Economics and Service. The countries were analyzed using cluster analysis, the keywords - using k-means and hierarchical method. Using morphological text analytics, it is possible to evaluate the image of the global Internet discussion and to estimate the level of adaptation to the conditions of the new technological order and level of social stress for each country. A social Global Discussion Model was constructed, which corresponds to the social instability trends according to “The Global Risks Report” provided by the World Economic Forum. Authors completed Morphological Big Data text analysis of the three types of development potential by R. S. Greenberg (natural, intellectual, spatial), which showed that Russia occupies a stable and promising position in comparison with a number of countries.