Discover knowledge of big data in social networks using machine learning

Abstract

Big data is the product of human collective intelligence, which has a high cost with the development of e-commerce in terms of complexity, semantics, distribution and processing in web-based computing, cloud computing and computing intelligence. Big data is important only when it becomes useful knowledge and information. In this study, using the technique of text mining and content analysis, the economic phenomena of 1998 in the social network LinkedIn are studied and examined and all published posts are included. ; 2800 posts in four groups; Inflation and increase in the cost of living and increase in the price of goods, increase in wages of labors and employees, increase in the unemployment rate, change in the exchange rate of classification and correlation between categories are described by the characteristics of users. User posts were analyzed using Rapidminer software and text mining algorithms, and in the end, we concluded that the number of users who have been involved in inflation and rising living costs and rising commodity prices, the highest number of users. And people who have been following the exchange rate change have had the most contacts.