Twitter Mining using R

Authors

  • Omkar Jagdale UG Scholar, Department of Computer Engineering Bharati Vidyapeeth College of Engineering Navi Mumbai, Maharashtra, India.
  • Vikrant Harmalkar UG Scholar, Department of Computer Engineering Bharati Vidyapeeth College of Engineering Navi Mumbai, Maharashtra, India.
  • Swati Chavan UG Scholar, Department of Computer Engineering Bharati Vidyapeeth College of Engineering Navi Mumbai, Maharashtra, India.
  • Prof. Nidhi Sharma Professor Department of Computer Engineering Bharati Vidyapeeth College of Engineering Navi Mumbai, Maharashtra, India.

Keywords:

Opinion, User Generated Content, Mining

Abstract

With the growing availability of user-generated contents (UGC), such as discussion forums, blog sites, Internet forums and social networks, public have multiple ways to mention their reviews, comments and make them available to everybody. Publicly open opinions provide valuable data for decision-making processes. Therefore, the computational treatment of sentiment and opinions has been regarded as a challenging field of research that can serve diverse purposes. In this, the various methods of mining in multiple ways such as web and data mining are used to retrieve data from web sites and to optimize we need to go through the queries of data mining. The proposed development of Opinion Mining is fundamentally intended to develop a system where users can get an optimized result for the different opinions on different products or services available on different e-commerce websites. This project mainly deals with evaluating different opinions so that we can get a quick idea of different views expressed by different users. Here, the data mining concepts are used which mainly deals with mining the UGC from different e-commerce websites which are being used in our daily routine life and after we extract the required UGC we need to prepare the definite opinion result using different data mining techniques.

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Published

2017-04-05

How to Cite

Twitter Mining using R. (2017). International Journal of Engineering Research and Advanced Technology (ijerat) (E-ISSN 2454-6135) DOI: 10.31695 IJERAT, 3(4), 17-22. https://ijerat.com/index.php/ijerat/article/view/217