Implementation of Text Mining in Socio-Economic Research

Author:

Malyshenko Konstantin1,Malyshenko Vadim1,Anashkina Marina1,Anashkin Dmitry2

Affiliation:

1. Humanitarian and Pedagogical Academy, Crimean Federal University Named After V.I. Vernadsky, Russia

2. Crimean Federal University Named After V.I. Vernadsky, Russia

Abstract

This work aims to analyze insights from social networks for identification of population satisfaction with pay level in Russia using the text mining approach. For this, a sentiment analysis framework was developed, which integrates Twitter mining tools and a sentiment index. Sentiments were extracted using Twitter mining and then recoded and substituted into the sentiment formula. The results of sentiment analysis indicate low satisfaction with levels of pay among Russians. Twitter was chosen as the object of research, as one of the most active and independent networks in Russia. It is possible that some of the tweets belong to authors who are not living in Russia at the moment, but their number is not significant and their interest in this issue, in the authors' opinion, only enhances the relevance of the problem under study.

Publisher

IGI Global

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