  Online microblogging services that have been increasingly used by people to
share and exchange information, have emerged as a promising way to profiling
multimedia contents, in a sense to provide users a socialized abstraction and
understanding of these contents. In this paper, we propose a microblogging
profiling framework, to provide a social demonstration of TV shows. Challenges
for this study lie in two folds: First, TV shows are generally offline, i.e.,
most of them are not originally from the Internet, and we need to create a
connection between these TV shows with online microblogging services; Second,
contents in a microblogging service are extremely noisy for video profiling,
and we need to strategically retrieve the most related information for the TV
show profiling.To address these challenges, we propose a MAP, a
microblogging-assisted profiling framework, with contributions as follows: i)
We propose a joint user and content retrieval scheme, which uses information
about both actors and topics of a TV show to retrieve related microblogs; ii)
We propose a social-aware profiling strategy, which profiles a video according
to not only its content, but also the social relationship of its microblogging
users and its propagation in the social network; iii) We present some
interesting analysis, based on our framework to profile real-world TV shows.
