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Data Mining and Association Rules to Determine Twitter Trends

Conference paper
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Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 181)

Abstract

Opinion mining has been widely studied in the last decade due to its great interest in the field of research and countless real-world applications. This research proposes a system that combines association rules, generalization of rules, and sentiment analysis to catalog and discover opinion trends in Twitter [1]. The sentiment analysis is used to favor the generalization of the association rules. In this sense, an initial set of 1.6 million tweets captured in an undirected way is first summarized through text mining in an input set for the algorithms of rules and sentiment analysis of 158,354 tweets. On this last group, easily interpretable standard and generalized sets of rules are obtained about characters, which were revealed as an interesting result of the system.

Keywords

Opinions mining Association rules Sentiment analysis Analysis of trends Unsupervised learning 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Universidad Peruana de Ciencias AplicadasLimaPerú
  2. 2.Universidad de la Costa (CUC)BarranquillaColombia
  3. 3.Universidad Tecnológica Centroamericana (UNITEC)San Pedro SulaHonduras
  4. 4.Corporación Universitaria minute de Dios. UNIMINUTOBarranquillaColombia
  5. 5.Corporación Universitaria LatinoamericanaBarranquillaColombia

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