  Twitter has become a leading source of real-time world-wide information and a
great medium for exploring emerging events, breaking news and general topics
which most matter to a broad audience. On the other hand, the explosive rate of
incoming information in Twitter leads users to experience information overload.
Whereas, a significant fraction of tweets are about news events, summarizing
the storyline of events can be helpful for users to easily access to the
relevant and key information hidden among tweets and thereby draw high level
conclusions. Storytelling is the task of providing chronological summaries of
significant sub-events development and sketching the relationship between
sub-events. In this paper, we propose a novel framework to generate a
summarized storyline of news events from social point of view. Utilizing the
concepts in graph-theory, we identify sub-events, summarize the evolution of
sub-events and generate a coherent storyline of them. Our approach models a
storyline as a directed tree of social salient sub-events evolving over time.
To overcome the enormous number of redundant tweets, we keep distilled
information in super-tweets. Experiments performed on a large scale data set
from tweets sent during the Iranian Presidential Election (#IranElection) and
the results demonstrate the efficiency and effectiveness of our framework.
