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Sensational News And News Maker Using Data Mining And Opinion Extraction

EasyChair Preprint no. 5978

4 pagesDate: July 1, 2021


The current outbreak and widespread of microblogging and social networking websites are reshaping many aspects of the modern day social interaction. Social Media today has exceeded the limits of entertainment or simple social interaction contexts. Social media now is better described as a living organism, that has a structure and a soul. The Social Media now reacts the pulse of the people; it reacts to their emotions, and interacts with their opinions. Analyzing and monitoring the content of Social Media can bring about some valuable insights, of which the conventional media means weren’t able to convey. Social Networking is the medium which allows million users to share their opinion, ideas, views and huge amount of data is presented for internet users and a lot of data generated too. This project proposes the paradigm to extract the sentiment from famous micro blogging service, called twitter. Twitter is one of the most popular portals, where people post their opinions, views for everything. In this project, data mining techniques are used to automatically classify the sentiments of Tweets taken from Twitter dataset. This project tackles the concept of sensational news and newsmaker detection within Twitter. The project identifies the dimensions of similarity and interaction between news and tweets that provides the tools to calculate sensational news maker and news.

Keyphrases: Datamining, Microblogging, Sentimental Analysis

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Aswathy Dhanapalan},
  title = {Sensational News And News Maker Using Data Mining And Opinion Extraction},
  howpublished = {EasyChair Preprint no. 5978},

  year = {EasyChair, 2021}}
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