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...
- 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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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. |
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2021 |
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2021-11-03T20:14:07Z |
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2021-06-03 |
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Trabajo de grado (Pregrado y/o Especialización) |
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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 |
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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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