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One of the major sources of trending news, events and opinion in the currentage is micro blogging. Twitter, being one of them, is extensively used to minedata about public responses and event updates. This paper intends to proposemethods to filter tweets to obtain the most accurately descriptive tweets,which communicates the content of the trend. It also potentially ranks thetweets according to relevance. The principle behind the ranking mechanism wouldbe the assumed tendencies in the natural language used by the users. Themapping frequencies of occurrence of words and related hash tags is used tocreate a weighted score for each tweet in the sample space obtained fromtwitter on a particular trend.

Mining and Analyzing Twitter trends: Frequency based ranking of descriptive Tweets