A Review on Identifying and Ranking Current News Topics

Authors

  • Neha Vijay Manwatkar  M.Tech Scholar, Department of Computer Science and Engineering Tulsiramji Gaikwad-Patil College of Engineering and Technology Nagpur, Maharashtra, India
  • Prof. Jayant Adhikari  Department of Computer Science and Engineering Tulsiramji Gaikwad-Patil College of Engineering and Technology Nagpur, Maharashtra, India
  • Prof. Rajesh Babu  Department of Computer Science and Engineering Tulsiramji Gaikwad-Patil College of Engineering and Technology Nagpur, Maharashtra, India

Keywords:

Information Filtering, Social Computing, Social Network Analysis, Topic Identification, Topic Ranking.

Abstract

Now a days, social media services such as Twitter huge amount of user-generated data, which has a great potential to contain informative news-related content, In present day times, internet based life administrations, for example, Twitter give a gigantic measure of client created information, which can possibly contain useful news-related substance. Twitter as a new form of social media can potentially contain much useful information, but content analysis on Twitter has not been well studied. Mass media sources such as news media used to inform us about daily events. For these assets to be helpful, we must find a way to filter noise and only capture the content that, in view of its closeness to the news media, is thought about significant. Be that as it may, even after noise is evacuated, data overload may even now exist in the rest of the information. Henceforth, it is advantageous to organize it for utilization. To accomplish prioritization, data must be positioned arranged by evaluated significance thinking about three variables. In the first place, the transient commonness of a specific point in the news media is a factor of significance, and can be viewed as the media center (MF) of a subject. Second, the fleeting predominance of the theme in social media demonstrates its client consideration (UA). Last, the communication between the internet based life clients who notice this theme demonstrates the quality of the network talking about it, and can be viewed as the client connection (UI) around the subject. We propose an unsupervised system SociRank which distinguishes news points common in both web-based social networking and the news media, and after that positions them by significance utilizing their degrees of MF, UA, and UI. Our analyses demonstrate that SociRank improves the quality and assortment of naturally recognized news points.

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International Journal of Scientific Research in Science and Technology

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Published

2019-04-30

Issue

Volume 6, Issue 2, March-April-2019

Section

Research Articles

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How to Cite

[1]
Neha Vijay Manwatkar, Prof. Jayant Adhikari, Prof. Rajesh Babu, " A Review on Identifying and Ranking Current News Topics, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 6, Issue 2, pp.412-419, March-April-2019.