Sentiment Polarity Detection in Social Networks: An Approach for Asthma Disease Management View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Harry Luna-Aveiga , José Medina-Moreira , Katty Lagos-Ortiz , Oscar Apolinario , Mario Andrés Paredes-Valverde , María del Pilar Salas-Zárate , Rafael Valencia-García

ABSTRACT

Asthma disease is a serious health problem that affects all age groups. Asthma-related hospitalizations and deaths have declined in some countries. However, the number of patients with symptoms has increased in the last years. Even though asthma patients have contact with health professionals, they must be an active part in treatment team. On the other hand, there has been an exponential growth of information about healthcare and diseases management on social networks such as Twitter. Aiming to benefit from this information, in this work we propose a method for detecting the emotional reaction of patients about asthma domain concepts such as physical activities, drugs, among others. The findings obtained from the analysis of such information can help to other patients to avoid habits that could harm their health. Our proposal was evaluated with a corpus of Twitter messages obtaining a precision of 82.95%, a recall of 82.27%, and F-measure of 82.36% in sentiment polarity identification. More... »

PAGES

141-152

References to SciGraph publications

Book

TITLE

Advanced Computational Methods for Knowledge Engineering

ISBN

978-3-319-61910-1
978-3-319-61911-8

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-61911-8_13

DOI

http://dx.doi.org/10.1007/978-3-319-61911-8_13

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1090277717


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