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|title: ||TVPulse: detecting TV highlights in Social Networks|
|authors: ||Vilaça, Afonso|
Aguiar, Rui L.
|issue date: ||Sep-2015|
|publisher: ||Instituto de Telecomunicações|
|abstract: ||Sharing live experiences in social networks is a growing trend. That includes posting comments and sentiments about TV programs. Automatic detection of messages with
contents related to TV allows a numerous quantity of applications in the industry of entertainment information.
This paper describes a system that is capable of detecting
TV highlights in one of the most important social networks - Twitter. Combining Twitter’s messages and information from an
Electronic Programming Guide (EPG) we built a model that matches tweets with TV programs with an accuracy over 80%. Our model required the construction of semantic profiles for the Portuguese language. These semantic profiles are used to identify
the most representative tweets as highlights of a TV program. Far from finished, we intend to further develop our system to take advantage of external metadata in order to improve matching rates.|
|publisher version/DOI: ||http://atnog.av.it.pt/content/tvpulse-detecting-tv-highlights-social-networks|
|source: ||10th Conference on Telecommunications Conftele|
|appears in collections||IT - Comunicações|
DETI - Comunicações
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