TweeProfiles: Detection of Spatio-temporal Patterns on Twitter

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2014

Autores

Cunha, T (Autor) Outra; Carlos Soares (Autor) FEUP; Rodrigues, EM (Autor) Outra

Ata de Conferência Internacional

Título: ADVANCED DATA MINING AND APPLICATIONS, ADMA 2014

Páginas: 123-136

10th International Conference on Advanced Data Mining and Applications (ADMA)

Guilin, PEOPLES R CHINA, DEC 19-21, 2014

Indexação

ISI Web of Knowledge - 4 Citações

Scopus - 5 Citações

Classificação Científica

CORDIS: Ciências Físicas > Ciência de computadores > Cibernética > Inteligência artificial

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-00A-1FK

DOI: 10.1007/978-3-319-14717-8_10

Abstract (EN): Online social networks present themselves as valuable information sources about their users and their respective behaviours and interests. Many researchers in data mining have analysed these types of data, aiming to find interesting patterns. This paper addresses the problem of identifying and displaying tweet profiles by analysing multiple types of data: spatial, temporal, social and content. The data mining process that extracts the patterns is composed by the manipulation of the dissimilarity matrices for each type of data, which are fed to a clustering algorithm to obtain the desired patterns. This paper studies appropriate distance functions for the different types of data, the normalization and combination methods available for different dimensions and the existing clustering algorithms. The visualization platform is designed for a dynamic and intuitive usage, aimed at revealing the extracted profiles in an understandable and interactive manner. In order to accomplish this, various visualization patterns were studied and widgets were chosen to better represent the information. The use of the project is illustrated with data from the Portuguese twittosphere.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 14