Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia

In this degree work, a sentiment analysis of the perception of COVID-19 vaccination in Colombia is carried out, taking as a source of data the publications on the social network Twitter. With the activities carried out, it was possible to obtain information on the Tweets from March 15 to April 25, 2...

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Autores:
Arias García, Héctor Leonardo
Doria Pérez, Luís Carlos
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2021
Institución:
Universidad Antonio Nariño
Repositorio:
Repositorio UAN
Idioma:
spa
OAI Identifier:
oai:repositorio.uan.edu.co:123456789/5160
Acceso en línea:
http://repositorio.uan.edu.co/handle/123456789/5160
Palabra clave:
Análisis de sentimientos
Minería de texto
COVID-19
Sentiment analysis
Text mining
COVID-19
Rights
openAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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network_name_str Repositorio UAN
repository_id_str
dc.title.es_ES.fl_str_mv Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia
title Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia
spellingShingle Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia
Análisis de sentimientos
Minería de texto
COVID-19
Sentiment analysis
Text mining
COVID-19
title_short Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia
title_full Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia
title_fullStr Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia
title_full_unstemmed Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia
title_sort Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en Colombia
dc.creator.fl_str_mv Arias García, Héctor Leonardo
Doria Pérez, Luís Carlos
dc.contributor.advisor.spa.fl_str_mv Cables Pérez, Elio Higinio
Neira Espitia, Edison Leonardo
dc.contributor.author.spa.fl_str_mv Arias García, Héctor Leonardo
Doria Pérez, Luís Carlos
dc.subject.es_ES.fl_str_mv Análisis de sentimientos
Minería de texto
COVID-19
topic Análisis de sentimientos
Minería de texto
COVID-19
Sentiment analysis
Text mining
COVID-19
dc.subject.keyword.es_ES.fl_str_mv Sentiment analysis
Text mining
COVID-19
description In this degree work, a sentiment analysis of the perception of COVID-19 vaccination in Colombia is carried out, taking as a source of data the publications on the social network Twitter. With the activities carried out, it was possible to obtain information on the Tweets from March 15 to April 25, 2021 through the streaming API provided by the social network, the information was stored in MongoDB databases in the cloud. Python was used as a programming language for the implementation of the source code by creating notebooks.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-11-03T20:14:07Z
dc.date.available.none.fl_str_mv 2021-11-03T20:14:07Z
dc.date.issued.spa.fl_str_mv 2021-06-03
dc.type.spa.fl_str_mv Trabajo de grado (Pregrado y/o Especialización)
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
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dc.identifier.uri.none.fl_str_mv http://repositorio.uan.edu.co/handle/123456789/5160
dc.identifier.bibliographicCitation.spa.fl_str_mv Alamoodi, A., Zaidan, B., Zaidan, A., Albahri, O., Mohammed, K., Malik, R., Almahdi, E., Chyad, M., Tareq, Z., Albahri, A., Hameed, H., & Alaa, M. (2021). Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review. 13
Bian, Y., Cui, K., Wang, L., Zheng, G., Guo, H., Yang, J., Jiang, M., & Lu, A. (2014)
IEEE International Conference on Bioinformatics and Biomedicine - Application of Acupuncture on Coronary Heart Disease Treatment: A Text Mining Study. 4. Bian, Y., Zhou, H., Guo, J., Wang, Y., Zheng, G., Guo, H., Tan, Y., Ren, X., Dong, R., Zhang, J., Cui, Z., Lu, A., Jiang, M., & Wang, Y. (2014). IEEE International Conference on Bioinformatics and Biomedicine, Study of acupuncture therapy on hypertension based on text ming. 4.
Bisong, E. (2019). Building Machine Learning and Deep Learning Models on Google Cloud Platform.
Caputo, A., Giacchetta, A., & Langher, V. (2016). AIDS as social construction: text mining of AIDSrelated information in the Italian press. 7
Chakraborty, K., Bhatia, S., Bhattacharyya, S., Platos, J., Bag, R., & Hassanien, A. (2020). Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media. ELSEVIER, 14.
Gonzalez Peña, D., Lourenço, A., López Fernández, H., Reboiro Jato, H., & Fdez Riverola, F. (2014, SEPTIEMBRE). Web scraping technologies in an API world - Briefings in Bioinformatics
Kabir, Y., & Madria, S. (2020, JULIO 11). CoronaVis: A Real-time COVID-19 Tweets Data Analyzer and Data Repository. 10.
KARAMI, A., LUNDY, M., WEBB, F., & DWIVEDI, Y. (2020). Twitter and Research: A Systematic Literature Review Through Text Mining. IEEE ACCESS.
Martinez, J. (2016). Primer Taller de Análisis de Sentimiento en Twitter con R. DB GUIDANCE. https://www.youtube.com/watch?v=nOIZnYLlPBo
dc.identifier.instname.spa.fl_str_mv instname:Universidad Antonio Nariño
dc.identifier.reponame.spa.fl_str_mv reponame:Repositorio Institucional UAN
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url http://repositorio.uan.edu.co/handle/123456789/5160
identifier_str_mv Alamoodi, A., Zaidan, B., Zaidan, A., Albahri, O., Mohammed, K., Malik, R., Almahdi, E., Chyad, M., Tareq, Z., Albahri, A., Hameed, H., & Alaa, M. (2021). Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review. 13
Bian, Y., Cui, K., Wang, L., Zheng, G., Guo, H., Yang, J., Jiang, M., & Lu, A. (2014)
IEEE International Conference on Bioinformatics and Biomedicine - Application of Acupuncture on Coronary Heart Disease Treatment: A Text Mining Study. 4. Bian, Y., Zhou, H., Guo, J., Wang, Y., Zheng, G., Guo, H., Tan, Y., Ren, X., Dong, R., Zhang, J., Cui, Z., Lu, A., Jiang, M., & Wang, Y. (2014). IEEE International Conference on Bioinformatics and Biomedicine, Study of acupuncture therapy on hypertension based on text ming. 4.
Bisong, E. (2019). Building Machine Learning and Deep Learning Models on Google Cloud Platform.
Caputo, A., Giacchetta, A., & Langher, V. (2016). AIDS as social construction: text mining of AIDSrelated information in the Italian press. 7
Chakraborty, K., Bhatia, S., Bhattacharyya, S., Platos, J., Bag, R., & Hassanien, A. (2020). Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media. ELSEVIER, 14.
Gonzalez Peña, D., Lourenço, A., López Fernández, H., Reboiro Jato, H., & Fdez Riverola, F. (2014, SEPTIEMBRE). Web scraping technologies in an API world - Briefings in Bioinformatics
Kabir, Y., & Madria, S. (2020, JULIO 11). CoronaVis: A Real-time COVID-19 Tweets Data Analyzer and Data Repository. 10.
KARAMI, A., LUNDY, M., WEBB, F., & DWIVEDI, Y. (2020). Twitter and Research: A Systematic Literature Review Through Text Mining. IEEE ACCESS.
Martinez, J. (2016). Primer Taller de Análisis de Sentimiento en Twitter con R. DB GUIDANCE. https://www.youtube.com/watch?v=nOIZnYLlPBo
instname:Universidad Antonio Nariño
reponame:Repositorio Institucional UAN
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Acceso abierto
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eu_rights_str_mv openAccess
dc.coverage.spatial.spa.fl_str_mv Colombia
dc.publisher.spa.fl_str_mv Universidad Antonio Nariño
dc.publisher.program.spa.fl_str_mv Especialización en Gobierno de Datos
dc.publisher.faculty.spa.fl_str_mv Facultad de Ingeniería de Sistemas
dc.publisher.campus.spa.fl_str_mv Bogotá - Federmán
institution Universidad Antonio Nariño
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spelling Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)Acceso abiertohttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Cables Pérez, Elio HiginioNeira Espitia, Edison LeonardoArias García, Héctor LeonardoDoria Pérez, Luís Carloshttps://orcid.org/0000-0003-4295-3902https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000073893https://scholar.google.com/citations?user=_T8_39QAAAAJ&hl=no1223202980512232028095Colombia2021-11-03T20:14:07Z2021-11-03T20:14:07Z2021-06-03http://repositorio.uan.edu.co/handle/123456789/5160Alamoodi, A., Zaidan, B., Zaidan, A., Albahri, O., Mohammed, K., Malik, R., Almahdi, E., Chyad, M., Tareq, Z., Albahri, A., Hameed, H., & Alaa, M. (2021). Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review. 13Bian, Y., Cui, K., Wang, L., Zheng, G., Guo, H., Yang, J., Jiang, M., & Lu, A. (2014)IEEE International Conference on Bioinformatics and Biomedicine - Application of Acupuncture on Coronary Heart Disease Treatment: A Text Mining Study. 4. Bian, Y., Zhou, H., Guo, J., Wang, Y., Zheng, G., Guo, H., Tan, Y., Ren, X., Dong, R., Zhang, J., Cui, Z., Lu, A., Jiang, M., & Wang, Y. (2014). IEEE International Conference on Bioinformatics and Biomedicine, Study of acupuncture therapy on hypertension based on text ming. 4.Bisong, E. (2019). Building Machine Learning and Deep Learning Models on Google Cloud Platform.Caputo, A., Giacchetta, A., & Langher, V. (2016). AIDS as social construction: text mining of AIDSrelated information in the Italian press. 7Chakraborty, K., Bhatia, S., Bhattacharyya, S., Platos, J., Bag, R., & Hassanien, A. (2020). Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media. ELSEVIER, 14.Gonzalez Peña, D., Lourenço, A., López Fernández, H., Reboiro Jato, H., & Fdez Riverola, F. (2014, SEPTIEMBRE). Web scraping technologies in an API world - Briefings in BioinformaticsKabir, Y., & Madria, S. (2020, JULIO 11). CoronaVis: A Real-time COVID-19 Tweets Data Analyzer and Data Repository. 10.KARAMI, A., LUNDY, M., WEBB, F., & DWIVEDI, Y. (2020). Twitter and Research: A Systematic Literature Review Through Text Mining. IEEE ACCESS.Martinez, J. (2016). Primer Taller de Análisis de Sentimiento en Twitter con R. DB GUIDANCE. https://www.youtube.com/watch?v=nOIZnYLlPBoinstname:Universidad Antonio Nariñoreponame:Repositorio Institucional UANrepourl:https://repositorio.uan.edu.co/In this degree work, a sentiment analysis of the perception of COVID-19 vaccination in Colombia is carried out, taking as a source of data the publications on the social network Twitter. With the activities carried out, it was possible to obtain information on the Tweets from March 15 to April 25, 2021 through the streaming API provided by the social network, the information was stored in MongoDB databases in the cloud. Python was used as a programming language for the implementation of the source code by creating notebooks.En el presente trabajo de grado se realiza un análisis de sentimiento de la percepción de la vacunación del COVID-19 en Colombia, tomando como fuente de datos las publicaciones en la red social Twitter. Con las actividades realizadas se logró obtener información de los Tweets desde el día 15 de marzo al día 25 de abril del año 2021 por medio de la API streaming proporcionada por la red social, se almaceno la información en bases de datos MongoDB en la nube. Se utilizó Python como lenguaje de programación para la implementación del código fuente mediante la creación de notebooks.Especialista en Gobierno de DatosEspecializaciónPresencialMonografíaspaUniversidad Antonio NariñoEspecialización en Gobierno de DatosFacultad de Ingeniería de SistemasBogotá - FedermánAnálisis de sentimientosMinería de textoCOVID-19Sentiment analysisText miningCOVID-19Análisis de sentimientos sobre la percepción ciudadana de la vacunación del COVID-19 en ColombiaTrabajo de grado (Pregrado y/o Especialización)http://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/version/c_970fb48d4fbd8a85EspecializadaORIGINAL2021_HéctorLeonardoAriasGarcía.pdf2021_HéctorLeonardoAriasGarcía.pdfTrabajo de grado de la Especializaciónapplication/pdf3654889https://repositorio.uan.edu.co/bitstreams/cba9e93d-0dd4-4a96-9ea6-42764e6e9ab2/downloadc4567b8fb8979f1c041cb468cb50815aMD512021_HéctorLeonardoAriasGarcía_Acta.pdf2021_HéctorLeonardoAriasGarcía_Acta.pdfActas de la 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