Artigo em revista científica Q1
MISNIS: an intelligent platform for Twitter topic mining
João Paulo Carvalho (Carvalho, J. P.); Hugo Hermogenes Lopes da Costa Rosa (Rosa, H.); Gaspar Brogueira (Brogueira, G.); Fernando Batista (Batista, F.);
Título Revista
Expert Systems with Applications
Ano
2017
Língua
Inglês
País
Reino Unido
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Abstract/Resumo
Twitter has become a major tool for spreading news, for dissemination of positions and ideas, and for the commenting and analysis of current world events. However, with more than 500 million tweets flowing per day, it is necessary to find efficient ways of collecting, storing, managing, mining and visualizing all this information. This is especially relevant if one considers that Twitter has no ways of indexing tweet contents, and that the only available categorization “mechanism” is the #hashtag, which is totally dependent of a user's will to use it. This paper presents an intelligent platform and framework, named MISNIS - Intelligent Mining of Public Social Networks’ Influence in Society - that facilitates these issues and allows a non-technical user to easily mine a given topic from a very large tweet's corpus and obtain relevant contents and indicators such as user influence or sentiment analysis. When compared to other existent similar platforms, MISNIS is an expert system that includes specifically developed intelligent techniques that: (1) Circumvent the Twitter API restrictions that limit access to 1% of all flowing tweets. The platform has been able to collect more than 80% of all flowing portuguese language tweets in Portugal when online; (2) Intelligently retrieve most tweets related to a given topic even when the tweets do not contain the topic #hashtag or user indicated keywords. A 40% increase in the number of retrieved relevant tweets has been reported in real world case studies. The platform is currently focused on Portuguese language tweets posted in Portugal. However, most developed technologies are language independent (e.g. intelligent retrieval, sentiment analysis, etc.), and technically MISNIS can be easily expanded to cover other languages and locations.
Agradecimentos/Acknowledgements
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Palavras-chave
Twitter,Intelligent topic mining,Fuzzy fingerprints,Text analytics,Sentiment analysis
  • Ciências da Computação e da Informação - Ciências Naturais
  • Engenharia Eletrotécnica, Eletrónica e Informática - Engenharia e Tecnologia
  • Economia e Gestão - Ciências Sociais
Registos de financiamentos
Referência de financiamento Entidade Financiadora
PTDC/IVC-ESCT/4919/2012 Fundação para a Ciência e a Tecnologia
PEst-OE/EEI/LA0021/2013 Fundação para a Ciência e a Tecnologia
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