ATWITTER TREND MINING SYSTEM

Abstract

Micro blogging is one of the main sources of trending news, events, and opinion in the modern day. One 
of them, Twitter, is often used to gather information on public comments and event updates. In order to 
find the tweets that most properly convey the trend's substance, this article will provide ways to filter 
tweets. It could also order the tweets based on their relevancy. The expected patterns in the users' 
natural language would serve as the basis for the rating process. A weighted score for each tweet in the 
sample space collected from Twitter is created using the mapping frequencies of word occurrence and 
associated hash tags for a certain trend.