INVESTIGADORES
ARMENTANO Marcelo Gabriel
congresos y reuniones científicas
Título:
Towards a Followee Recommender System for Information Seeking Users in Twitter
Autor/es:
ARMENTANO, M. G.; GODOY, D. L.; AMANDI, A. A.
Lugar:
Girona
Reunión:
Workshop; Workshop on Semantic Adaptive Social Web 2011 in connection with the 19th International Conference on User Modeling, Adaptation and Personalization, UMAP 2011; 2011
Resumen:
Micro-blogging activity taking place in sites such as Twitter gains everyday more importance as a source of real-time information and news spreading medium. Finding relevant information sources among the increasing number of Twitter members is essential for users needing to cope with real-time information. In this paper we study Twitter aiming at generating a set of recommendations to a target user consisting in people who publish tweets that might be interesting to him/her. We evaluate and compare two recommendation approaches: the first selects a set of candidate recommendations using only the network topology and the second exploits the user-generated content available in their tweets.We report the results of a set of controlled experiments with real users carried out to evaluate and compare the performance of both algorithms.