<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2307-2113</journal-id>
<journal-title><![CDATA[Revista Cubana de Información en Ciencias de la Salud]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. cuba. inf. cienc. salud]]></abbrev-journal-title>
<issn>2307-2113</issn>
<publisher>
<publisher-name><![CDATA[Centro Nacional de Información de Ciencias MédicasEditorial Ciencias Médicas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2307-21132023000100026</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Análisis de sentimientos y tópicos sobre las vacunas cubanas Soberana 02 y Abdala en Twitter]]></article-title>
<article-title xml:lang="en"><![CDATA[Sentiment and topics analysis about the cuban vaccines Soberana 02 and Abdala on Twitter]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Rodríguez Sánchez]]></surname>
<given-names><![CDATA[Antonio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Rivero González]]></surname>
<given-names><![CDATA[Luis Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Soca Lozano]]></surname>
<given-names><![CDATA[Sandra]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Escuela Nacional de Salud Pública Departamento de Bioestadística ]]></institution>
<addr-line><![CDATA[ La Habana]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de La Habana Facultad de Derecho ]]></institution>
<addr-line><![CDATA[ La Habana]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad del Sur de la Florida Escuela de Psicología ]]></institution>
<addr-line><![CDATA[ Florida]]></addr-line>
<country>Estados Unidos</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2023</year>
</pub-date>
<volume>34</volume>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S2307-21132023000100026&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S2307-21132023000100026&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S2307-21132023000100026&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN El análisis de sentimientos o minería de opiniones es una rama de la computación que permite analizar opiniones, sentimientos y emociones en ciertas áreas de interés social como productos, servicios, organizaciones, compañías, eventos y temas de interés actual. En tal sentido se propuso identificar los sentimientos y tópicos presentes en los tweets que hicieron mención a las vacunas cubanas Soberana 02 y Abdala en la red social Twitter. Se optó por los lenguajes de programación Python y R con sus librerías específicas para la ciencia de datos. La primera parte del estudio, que abarcó desde el web scraping hasta la cuantificación de las palabras más usadas, se realizó con Python y las siguientes librerías: tweepy, pandas, re, nltk y matplotlib. Mientras que la segunda, que fue la del análisis de sentimientos y detección de tópicos, se implementó con R y se utilizó: tokenizers, tm, syuzhet, topic modeling, tidyverse, barplot y wordcloud. Se obtuvo que entre los términos con que más se dialoga en Twitter están dosis, vacunas, eficacia, cubanos, candidatos, millones, país, personas, recibido y población. En los tweets las emociones predominantes fueron el miedo y, ligeramente por encima, la confianza; en la polaridad predominó la positiva, como expresión del contexto vivido en el cual se desarrolló la campaña de vacunación. A partir de los tópicos identificados y los términos que se relacionaron con las emociones predominantes, así como por la polaridad, se aprecia consenso en torno a las vacunas Soberana 02 y Abdala.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Sentiment analysis or opinion mining is a branch of computing that allows analyzing opinions, feelings and emotions in certain areas of social interest such as products, services, organizations, companies, events and topics of current interest. In this sense, the objective of this paper was to identify the feelings and topics present in the tweets mentioning the Cuban vaccines Soberana 02 and Abdala on Twitter social network. The programming languages Python and R with their specific libraries for data science were chosen. The first part of the study, which ranged from web scraping to the quantification of the most used words, was carried out with Python and the libraries tweepy, pandas, re, nltk and matplotlib. While the second, which was the sentiment analysis and topic detection, was implemented with R and used tokenizers, tm, syuzhet, topic modeling, tidyverse, barplot, and wordcloud. It was obtained that among the terms with which there is more dialogue on Twitter are doses, vaccines, efficacy, Cubans, candidates, millions, country, people, received and population. In the tweets, the predominant emotions were fear and confidence, slightly above it; in the polarity, the positive one predominated, as an expression of the lived context in which the vaccination campaign was developed. A consensus can be perceived around the vaccines Soberana 02 and Abdala, from the identified topics and the terms that were related to the predominant emotions, as well as the polarity.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[análisis de sentimientos]]></kwd>
<kwd lng="es"><![CDATA[tópicos]]></kwd>
<kwd lng="es"><![CDATA[procesamiento de lenguaje natural]]></kwd>
<kwd lng="es"><![CDATA[Twitter]]></kwd>
<kwd lng="es"><![CDATA[vacunas]]></kwd>
<kwd lng="en"><![CDATA[sentiment analysis]]></kwd>
<kwd lng="en"><![CDATA[topics]]></kwd>
<kwd lng="en"><![CDATA[natural language processing]]></kwd>
<kwd lng="en"><![CDATA[Twitter]]></kwd>
<kwd lng="en"><![CDATA[vaccines]]></kwd>
</kwd-group>
</article-meta>
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