@misc{10481/62346,
year = {2020},
month = {4},
url = {http://hdl.handle.net/10481/62346},
abstract = {Pattern mining has been widely studied in the last decade given its great interest for research and its numerous applications in the real world. In this paper the definition of query and non-query based systems is proposed, highlighting the needs of non-query based systems in the era of Big Data. For this, we propose a new approach of a non-query based system that combines association rules, generalized rules and sentiment analysis in order to catalogue and discover opinion patterns in the social network Twitter. Association rules have been previously applied for sentiment analysis, but in most cases, they are used once the process of sentiment analysis is finished to see which tokens appear commonly related to a certain sentiment. On the other hand, they have also been used to discover patterns between sentiments. Our work differs from these in that it proposes a non-query based system which combines both techniques, in a mixed proposal of sentiment analysis and association rules to discover patterns and sentiment patterns in microblogging texts. The obtained rules generalize and summarize the sentiments obtained from a group of tweets about any character, brand or product mentioned in them. To study the performance of the proposed system, an initial set of 1.7 million tweets have been employed to analyse the most salient sentiments during the American pre-election campaign. The analysis of the obtained results supports the capability of the system of obtaining association rules and patterns with great descriptive value in this use case. Parallelisms can be established in these patterns that match perfectly with real life events.},
organization = {COPKIT Project, through the European Union's Horizon 2020 Research and Innovation Programme 	
786687},
organization = {Spanish Ministry for Economy and Competitiveness 	
TIN2015-64776-C3-1-R},
organization = {Andalusian Government, through Data Analysis in Medicine: from Medical Records to Big Data Project 	
P18-RT-2947},
organization = {Spanish Ministry of Education, Culture, and Sport 	
FPU18/00150},
organization = {University of Granada},
publisher = {IEEE},
keywords = {Query systems},
keywords = {Non-query systems},
keywords = {Pattern mining},
keywords = {Association rules},
keywords = {Sentiment analysis},
keywords = {Social media mining},
title = {Non-Query-Based Pattern Mining and Sentiment Analysis for Massive Microblogging Online Texts},
doi = {10.1109/ACCESS.2020.2990461},
author = {Díaz García, José Ángel and Ruiz Medina, María Dolores and Martín Bautista, María José},
}