Journalistic Relevance Classification in Social Network Messages: an Exploratory Approach

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2017

Autores

Sandim, M (Autor) Outra; Fortuna, P (Autor) Outra; Figueira, A (Autor) FCUP; Oliveira, L (Autor) Outra

Ata de Conferência Internacional

Título: COMPLEX NETWORKS & THEIR APPLICATIONS V

Páginas: 631-642

5th International Workshop on Complex Networks and their Applications (COMPLEX NETWORKS)

Univ Milan, Milan, ITALY, NOV 30-DEC 02, 2016

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 6 Citações

Outras Informações

ID Authenticus: P-00M-BH7

DOI: 10.1007/978-3-319-50901-3_50

Abstract (EN): Social networks are becoming a wide repository of information, some of which may be of interest for general audiences. In this study we investigate which features may be extracted from single posts propagated throughout a social network, and that are indicative of its relevance, from a journalistic perspective. We then test these features with a set of supervised learning algorithms in order to evaluate our hypothesis. The main results indicate that if a text fragment is pointed out as being interesting, meaningful for the majority of people, reliable and with a wide scope, then it is more likely to be considered as relevant. This approach also presents promising results when validated with several well-known learning algorithms.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12