  One of the major sources of trending news, events and opinion in the current
age is micro blogging. Twitter, being one of them, is extensively used to mine
data about public responses and event updates. This paper intends to propose
methods to filter tweets to obtain the most accurately descriptive tweets,
which communicates the content of the trend. It also potentially ranks the
tweets according to relevance. The principle behind the ranking mechanism would
be the assumed tendencies in the natural language used by the users. The
mapping frequencies of occurrence of words and related hash tags is used to
create a weighted score for each tweet in the sample space obtained from
twitter on a particular trend.
