Title of article :
Investigation of Trends and Analysis of Hidden New Patterns in Prominent News Agencies of Iran Using Data Mining and Text Mining Algorithms
Author/Authors :
sohrabi, babak university of tehran - faculty of management, Tehran, Iran , raeesi vanani, iman allameh tabataba i university - faculty of management and accounting, Tehran, Iran , namavar, meysam university of tehran - faculty of management, Tehran, Iran
From page :
114
To page :
137
Abstract :
These days, every business is trying to achieve its competitive goals. In other words, if one business uses the most modern analytical technologies optimally, it will certainly boost itssuccess level at an exponential rate. The Islamic Republic News Agency (IRNA) is one suchmass media industry that, according to its need, uses the benefits information technology (IT)provides it with. News flows, surveys, human resource management, warehouse management, software are key parts of the agency’s news penetration criteria. There is little software that focuses on analytical solutions for running the business optimally. This paper, among available text mining methods, intends to present the most important keywords of news texts based on weighing of words and their correlations, news classification, news sentiments, news trends in order to provide insights and patterns for future scholars and practitioners in the field. This approach will help news agencies maintain their competitive edge as well as predict and react to the market of news search and provision in a timely context-based manner.
Keywords :
News agency , Data mining , Text mining , Word correlation , Analytics
Journal title :
Webology
Journal title :
Webology
Record number :
2680491
Link To Document :
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