Implementation of Text Mining in Socio-Economic Research

被引:0
作者
Malyshenko, Konstantin [1 ]
Malyshenko, Vadim [1 ]
Anashkina, Marina [1 ]
Anashkin, Dmitry [2 ]
机构
[1] Crimean Fed Univ, Humanitarian & Pedag Acad, Dept Econ & Finance, Inst Econ & Management, Jalta, Russia
[2] Crimean Fed Univ, Dept Math Theory & Methods Teaching Math, Jalta, Russia
基金
俄罗斯科学基金会;
关键词
Big Data; Content; Data Mining; Mood Index; Sentiment Analysis; CONSUMER;
D O I
10.4018/IJBDCN.341263
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
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页数:21
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