Abstract:
Online Journalism is being seen as future of
Journalism. News Professionals are vying to
capture newsworthy stories that emerge from
crowd. Live Social Media especially Twitter
is generating enormous volumes of data every
minute. It becomes difficult to select credible
and relevant tweets that may form quality
news among others. The problem intensifies
due to the freedom of Twitter being an informal
language. Generating headlines by solving
this problem may still not be relevant and
may face the question of authenticity. Given a
set of keywords and a time period this problem
becomes manageable and can be solved efficiently.
We propose a bipartite algorithm that
clusters authentic tweets based on key phrases
and ranks the clusters based on trends in each
timeslot.