Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto

diagramas

Autores:: García Alzate, Daniel

Tipo de recurso:

Fecha de publicación:: 2022

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

id	UNACIONAL2_554956aea5bc274ecb19d99966be16ea
oai_identifier_str	oai:repositorio.unal.edu.co:unal/82298
network_acronym_str	UNACIONAL2
network_name_str	Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv	Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto
dc.title.translated.eng.fl_str_mv	Monitoring of femicide cases in Colombia using text mining techniques
title	Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto
spellingShingle	Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto 000 - Ciencias de la computación, información y obras generales::003 - Sistemas Minería de texto y de datos Violencia contra la mujer Violencia feminicida Minería de texto Violencia contra la mujer Extracción de información Caracterización de violencia feminicida en Colombia Femicide violence Text mining Violence against women Information extraction Characterization of femicide violence in Colombia
title_short	Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto
title_full	Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto
title_fullStr	Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto
title_full_unstemmed	Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto
title_sort	Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto
dc.creator.fl_str_mv	García Alzate, Daniel
dc.contributor.advisor.none.fl_str_mv	Villa Garzón, Fernán Alonso
dc.contributor.author.none.fl_str_mv	García Alzate, Daniel
dc.subject.ddc.spa.fl_str_mv	000 - Ciencias de la computación, información y obras generales::003 - Sistemas
topic	000 - Ciencias de la computación, información y obras generales::003 - Sistemas Minería de texto y de datos Violencia contra la mujer Violencia feminicida Minería de texto Violencia contra la mujer Extracción de información Caracterización de violencia feminicida en Colombia Femicide violence Text mining Violence against women Information extraction Characterization of femicide violence in Colombia
dc.subject.other.none.fl_str_mv	Minería de texto y de datos
dc.subject.lemb.none.fl_str_mv	Violencia contra la mujer
dc.subject.proposal.spa.fl_str_mv	Violencia feminicida Minería de texto Violencia contra la mujer Extracción de información Caracterización de violencia feminicida en Colombia
dc.subject.proposal.eng.fl_str_mv	Femicide violence Text mining Violence against women Information extraction Characterization of femicide violence in Colombia
description	diagramas
publishDate	2022
dc.date.accessioned.none.fl_str_mv	2022-09-16T18:44:54Z
dc.date.available.none.fl_str_mv	2022-09-16T18:44:54Z
dc.date.issued.none.fl_str_mv	2022
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TM
status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/82298
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/82298 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.references.spa.fl_str_mv	Abbasi, A., & Chen, H. (2007). Affect intensity analysis of dark web forums. ISI 2007: 2007 IEEE Intelligence and Security Informatics, 282–288. https://doi.org/10.1109/isi.2007.379486 Allister Simanjuntak, D., & Satriyo Nugroho, A. (2010). Text Classification Techniques used to facilitate Cyber Terrorism Investigation. IEEE Computer Society. Alsaif, H., & Alotaibi, T. (2019). Arabic Text Classification using Feature-Reduction Techniques for Detecting Violence on Social Media. Amrit, C., Paauw, T., Aly, R., & Lavric, M. (2017). Identifying child abuse through text mining and machine learning. Expert Systems with Applications, 88, 402–418. https://doi.org/10.1016/j.eswa.2017.06.035 Árevalo Mutiz, P. L. (2018, March 2). Feminicidio en Colombia: avances y retos. https://www.urosario.edu.co/Periodico-NovaEtVetera/Sociedad/Feminicidio-en-Colombia-avances-y-retos/ Asik, G. A., & Nas Ozen, E. (2021). It takes a curfew: The effect of Covid-19 on female homicides. Economics Letters, 200, 109761. https://doi.org/10.1016/j.econlet.2021.109761 Ayuda en Acción. (2018, July 5). Tipos de violencia contra las mujeres \| Violencia de género. https://ayudaenaccion.org/ong/blog/mujer/tipos-violencia-mujeres/ Busso, L., Combei, C. R., & Tordini, O. (2021). Narrating Gender Violence A Corpus-Based Study on the Representation of Gender-Based Violence in Italian Media. Language, Gender and Hate Speech A Multidisciplinary Approach, 39–58. https://doi.org/10.30687/978-88-6969-478-3/002 Camelot: PDF Table Extraction for Humans — Camelot 0.10.1 documentation. (n.d.). Retrieved May 12, 2022, from https://camelot-py.readthedocs.io/en/master/ Choi, Y. J., Jeon, B. J., & Kim, H. W. (2020). Identification of key cyberbullies: A text mining and social network analysis approach. Telematics and Informatics, June, 101504. https://doi.org/10.1016/j.tele.2020.101504 Congreso de la República, C. (2008). Ley 1257 de 2008. Crimen de líder campesino Álvaro Narváez junto a su familia en el Cauca - Otras Ciudades - Colombia - ELTIEMPO.COM. (n.d.). Retrieved May 29, 2022, from https://www.eltiempo.com/colombia/otras-ciudades/crimen-de-lider-campesino-alvaro-narvaez-junto-a-su-familia-en-el-cauca-490528 Cronología de las masacres en Colombia durante el año 2020 (Enero a Agosto) DIPAZ. (n.d.). Retrieved May 29, 2022, from https://dipazcolombia.org/masacres-colombia-2020-enero-agosto/ E. Perron, B., G. Victor, B., Bushman, G., Moore, A., P. Ryan, J., Jiahong Lu, A., & K. Piellusch, E. (2019). Detecting substance-related problems in narrative investigation summaries of child abuse and neglect using text mining and machine learning. Child Abuse & Neglect. El Ansari, O., Jihad, Z., & Hajar, M. (2020). A dataset to support sexist content detection in arabic text. In Lecture Notes in Computer Science: Vol. 12119 LNCS. Springer International Publishing. https://doi.org/10.1007/978-3-030-51935-3_14 El Tiempo. (2020, July 7). CreanSistema de Prevención Temprana de violencias contra las mujeres - Gobierno - Política - ELTIEMPO.COM. https://www.eltiempo.com/politica/gobierno/gobierno-anuncia-sistema-de-prevencion-de-violencia-contra-las-mujeres-515256 Fiscalía General de la Nación. (n.d.). Retrieved January 9, 2021, from https://www.fiscalia.gov.co/colombia/ Gil, V. D., Betancur, J. D., Puerta, I. C., Montoya, L. M., & Sepulveda, J. M. (2018). the Femicide in Colombia and Mexico: a Text Mining Analysis. The Turkish Online Journal of Design, Art and Communication, 2018(March), 170–177. https://doi.org/10.7456/1080mse/021 Greenawald, B., Liu, Y., Wert, G., Al Boni, M., & Brown, D. E. (n.d.). A Comparison of Language-Dependent and Language-Independent Models for Violence Prediction. Gupta, V., & Lehal Professor, G. S. (2009). A Survey of Text Mining Techniques and Applications. www.alerts.yahoo.com Ham, E., & Jeong, S. (2021). an Analysis of Korea Newspaper Reporting on Intimate Partner Violence. 58(October 2020), 2692–2700. Hearst, M. (2003). What Is Text Mining? Henshaw, A. (2020). ‘ Peace with a Woman ’ s Face ’: Women , Social Media and the Colombian Peace Process. 42(3), 515–538. Hernández, J., Jiménez, D., Zagal, R., Mata, F., & Borges, J. A. L. (2021). Analysis of the Level of Geographic Criminal Risk Oriented to Women. In Communications in Computer and Information Science: Vol. 1430 CCIS. Springer International Publishing. https://doi.org/10.1007/978-3-030-89586-0_19 Home Page - Portal OCM. (n.d.). Retrieved January 9, 2021, from http://www.observatoriomujeres.gov.co/ Humberto, F., Murillo, S., Chica, J., Rodríguez, A., & Cortázar, G. De. (2018). The spatial heterogeneity of factors of feminicide : The case of Antioquia- Colombia. Applied Geography, 92(November 2016), 63–73. https://doi.org/10.1016/j.apgeog.2018.01.006 Iezzi, D. (2013). Italian Women In The New Millennium: Emancipated Or Violated? An Analysis Of Webmining On Fatal Domestic Violence. Rivista Italiana Di Economia Demografia e Statistica, LXVII(1992). http://www.sieds.it/listing/RePEc/journl/2013LXVII_N2_09_IEZZI.pdf Inicio - Instituto Nacional de Medicina Legal y Ciencias Forenses. (n.d.). Retrieved January 9, 2021, from https://www.medicinalegal.gov.co/ jaro-winkler · PyPI. (n.d.). Retrieved May 20, 2022, from https://pypi.org/project/jaro-winkler/ KADIC, N. (2019). TWITTER RESISTANCE AND DIGITAL TESTIMONIO(S) IN 140 CHARACTERS: RESTORING THE COMPLEXITY OF MEXICO’S HASHTAG FEMINISM. In Copyright by NEIRA KADIC 2019 (Vol. 3). UNIVERSITY OF OKLAHOMA. Karami, A., White, C. N., Ford, K., Swan, S., & Spinel, M. Y. (2020). Unwanted advances in higher education:Uncovering sexual harassment experiences in academia with text mining. Elsevier. Karystianis, G., Adily, A., Schofield, P., Knight, L., Galdon, C., Greenberg, D., Jorm, L., Nenadic, G., & Butler, T. (2019). Automatic Extraction of Mental Health Disorders From Domestic Violence Police Narratives : Text Mining Study. Journal of Medical Internet Research, 20(9), 1–16. https://doi.org/10.2196/11548 Karystianis, G., Adily, A., Schofield, P. W., Greenberg, D., Jorm, L., Nenadic, G., & Butler, T. (2019). Automated Analysis of Domestic Violence Police Reports to Explore Abuse Types and Victim Injuries : Text Mining Study. Journal of Medical Internet Research, 21, 1–12. https://doi.org/10.2196/13067 Karystianis, G., Simpson, A., Adily, A., Schofield, P., Greenberg, D., Wand, H., Nenadic, G., & Butler, T. (2020). Prevalence of Mental Illnesses in Domestic Violence Police Records : Text Mining Study. Journal of Medical Internet Research, 22. https://doi.org/10.2196/23725 Khandokar, I. A., Mamun, I., Chadni, T. I. A., Anas, Z. A., & Shatabda, S. (2020). Event Detection and Knowledge Mining from Unlabelled Bengali News Articles. ETCCE 2020 - International Conference on Emerging Technology in Computing, Communication and Electronics. https://doi.org/10.1109/ETCCE51779.2020.9350891 Li, J., & Dong, D. (2019). Keyword Analysis and Topic Extraction of Hospital Violence News. Computer Science & Education. Mohan, V. (n.d.). Preprocessing Techniques for Text Mining-An Overview Privacy Preserving Data Mining View project. Retrieved November 29, 2020, from https://www.researchgate.net/publication/339529230 Mouhssine, E., & Khalid, C. (2019). Social Big Data Mining Framework for Extremist Content Detection in Social Networks. International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2018 - Proceedings. https://doi.org/10.1109/ISAECT.2018.8618726 Naciones Unidas. (1993). Declaración sobre la Eliminación de la Violencia contra la Mujer. Niklander, S., & Niklander, G. (2017). Combining sentimental and content analysis for recognizing and interpreting human affects. Communications in Computer and Information Science, 713, 465–468. https://doi.org/10.1007/978-3-319-58750-9_64 O’halloran, K. L., Tan, S., Wignell, P., Bateman, J. A., Pham, D. S., Grossman, M., & Vande Moere, A. (2016). Interpreting text and image relations in violent extremist discourse: A mixed methods approach for big data analytics. Terrorism and Political Violence, 31(3), 454–474. https://doi.org/10.1080/09546553.2016.1233871 Observatorio Feminicidios Colombia. (n.d.). Retrieved January 9, 2021, from https://observatoriofeminicidioscolombia.org/ ONU. (n.d.-a). Cómo trabajamos: Eliminación de la violencia contra las mujeres \| ONU Mujeres – Colombia. Retrieved November 14, 2020, from https://colombia.unwomen.org/es/como-trabajamos/violencia-contra-las-mujeres ONU. (n.d.-b). Feminicidio \| ONU Mujeres – Colombia. Retrieved October 25, 2020, from https://colombia.unwomen.org/es/como-trabajamos/violencia-contra-las-mujeres/feminicidio ONU. (2017). Colombia se unió para decir basta al feminicidio: Ni Una Menos \| ONU Mujeres – Colombia. https://colombia.unwomen.org/es/noticias-y-eventos/articulos/2017/11/exposicionfem Öztürk, N., & Ayvaz, S. (2018). Sentimental analysis on Twitter: A text mining approach to the Syrian refugee crisis. Telematics and Informatics, 136–147. Paulino da Costa, J., Barbosa dos Santos, T. A. M., Carvalho da Mata, E., Silva da Silva, M., & Lisboa Francês, C. R. (2019). DEEP LEARNING : APPLICATION OF THE LSTM MODEL IN THE CATEGORIZATION OF TWEETS ON VIOLENCE IN THE CITY OF BELÉM. ResearchGate, July 2020. https://doi.org/10.33965/bigdaci2019 pdfminer.six. (n.d.). Converting a PDF file to text. Retrieved April 23, 2022, from https://pdfminersix.readthedocs.io/en/latest/topic/converting_pdf_to_text.html Pedraza, G., & María Rodríguez, A. (2016). EL CORTO RECORRIDO DEL FEMINICIDIO EN COLOMBIA. In UNA Revista de Derecho (Vol. 1). Poelmans, J., Elzinga, P., Viaene, S., & Dedene, G. (2011). Formally analysing the concepts of domestic violence. Expert Systems With Applications, 38(4), 3116–3130. https://doi.org/10.1016/j.eswa.2010.08.103 Poelmans, J., M. Van Hulle, M., Viaene, S., Elzinga, P., & Dedene, G. (2011). Text mining with emergent self organizing maps and multi-dimensional scaling: A comparative study on domestic violence. Applied Soft Computing. Policía Nacional de Colombia. (n.d.). Retrieved January 9, 2021, from https://www.policia.gov.co/ PyPDF2 · PyPI. (n.d.). Retrieved May 12, 2022, from https://pypi.org/project/PyPDF2/ Sabbah, T., Selamat, A., Ibrahim, R., & Fujita, H. (2016). Neurocomputing Hybridized term-weighting method for Dark Web classification. 173, 1908–1926. https://doi.org/10.1016/j.neucom.2015.09.063 scikit-learn: machine learning in Python — scikit-learn 1.1.1 documentation. (n.d.). Retrieved May 21, 2022, from https://scikit-learn.org/stable/ Secretaría Distrital de la Mujer. (n.d.). Tres años de la Ley de Feminicidio. \| Secretaría Distrital de la Mujer. Retrieved October 25, 2020, from http://www.sdmujer.gov.co/noticias/tres-años-la-ley-feminicidio Sistema Integrado de Información de Violencias de Género. (n.d.). Retrieved January 9, 2021, from http://onviolenciasgenero.minsalud.gov.co/Paginas/sivige.aspx spaCy · Industrial-strength Natural Language Processing in Python. (n.d.). Retrieved May 21, 2022, from https://spacy.io/ Sukanya, M., & Biruntha, S. (2012). Techniques on text mining. Proceedings of 2012 IEEE International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2012, 978, 269–271. https://doi.org/10.1109/ICACCCT.2012.6320784 tabula-py · PyPI. (n.d.). Retrieved May 12, 2022, from https://pypi.org/project/tabula-py/ Ul Rehman, Z., Abbas, S., Khan, M. A., Mustafa, G., Fayyaz, H., Hanif, M., & Saeed, M. A. (2020). Understanding the language of ISIS: An empirical approach to detect radical content on twitter using machine learning. Computers, Materials and Continua, 66(2), 1075–1090. https://doi.org/10.32604/cmc.2020.012770 Vanguardia. (2020, June 27). Ocho medidas del Estado para proteger a las mujeres \| Vanguardia.com. https://www.vanguardia.com/colombia/ocho-medidas-del-estado-para-proteger-a-las-mujeres-YE2547634 Varela, N., Gálvez Valega, J. A., & Pineda Lezama, O. B. (2020). Analysis of behavior of automatic learning algorithms to identify criminal messages. Procedia Computer Science, 175, 114–119. https://doi.org/10.1016/j.procs.2020.07.019 ViceColombia. (2020, June 26). Gobierno arrecia medidas para frenar violencia contra las mujeres. https://mlr.vicepresidencia.gov.co/Paginas/prensa/2020/Gobierno-arrecia-medidas-para-frenar-violencia-contra-las-mujeres.aspx Wang, S. H., Ding, Y., Zhao, W., Huang, Y. H., Perkins, R., Zou, W., & Chen, J. J. (2016). Text mining for identifying topics in the literatures about adolescent substance use and depression. BMC Public Health, 16(1), 4–11. https://doi.org/10.1186/s12889-016-2932-1 Watts, C., & Zimmerman, C. (2002). Violence against women: Global scope and magnitude. In Lancet (Vol. 359, Issue 9313, pp. 1232–1237). https://doi.org/10.1016/S0140-6736(02)08221-1 Wilson, M., Spike, E., Karystianis, G., & Butler, T. (2021). Nonfatal Strangulation During Domestic Violence Events in New South Wales: Prevalence and Characteristics Using Text Mining Study of Police Narratives. Violence Against Women. https://doi.org/10.1177/10778012211025993 wordcloud · PyPI. (n.d.). Retrieved May 21, 2022, from https://pypi.org/project/wordcloud/ Xuan Koh, J., & Ming Liew, T. (2020). How loneliness is talked about in social media during COVID-19 pandemic: Text mining of 4,492 Twitter feeds. Journal of Psychiatric Research. Xue, J., Chen, J., & Gelles, R. (2019). Using Data Mining Techniques to Examine Domestic Violence Topics on Twitter. Violence and Gender, 6(2), 105–114. https://doi.org/10.1089/vio.2017.0066 Ye In Hwang, J., Zheng, L., Karystiansis, G., Gibbs, V., Sharp, K., & Butler, T. (2020). Domestic violence events involving autism: a text mining study of police records in New South Wales, 2005-2016. Research in Autism Spectrum Disorders.
dc.rights.coar.fl_str_mv	http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv	Reconocimiento 4.0 Internacional
dc.rights.uri.spa.fl_str_mv	http://creativecommons.org/licenses/by/4.0/
dc.rights.accessrights.spa.fl_str_mv	info:eu-repo/semantics/openAccess
rights_invalid_str_mv	Reconocimiento 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv	openAccess
dc.format.extent.spa.fl_str_mv	81 páginas
dc.format.mimetype.spa.fl_str_mv	application/pdf
dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Medellín - Minas - Maestría en Ingeniería - Analítica
dc.publisher.department.spa.fl_str_mv	Departamento de la Computación y la Decisión
dc.publisher.faculty.spa.fl_str_mv	Facultad de Minas
dc.publisher.place.spa.fl_str_mv	Medellín, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Medellín
institution	Universidad Nacional de Colombia
bitstream.url.fl_str_mv	https://repositorio.unal.edu.co/bitstream/unal/82298/1/license.txt https://repositorio.unal.edu.co/bitstream/unal/82298/2/1036955423.2022.pdf https://repositorio.unal.edu.co/bitstream/unal/82298/3/1036955423.2022.pdf.jpg
bitstream.checksum.fl_str_mv	b577153cc0e11f0aeb5fc5005dc82d8a b1f8a89d290c3078b5893e4e698e7953 fafafb41a1b743837e0652d6bf988d06
bitstream.checksumAlgorithm.fl_str_mv	MD5 MD5 MD5
repository.name.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
repository.mail.fl_str_mv	repositorio_nal@unal.edu.co
_version_	1814089272351784960
spelling	Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Villa Garzón, Fernán Alonso9c83ea56495b8f17a79c27fd0001bb81García Alzate, Daniel85d9a3b0c6968306dd89fb5423f2b8a12022-09-16T18:44:54Z2022-09-16T18:44:54Z2022https://repositorio.unal.edu.co/handle/unal/82298Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/diagramasEn el presente trabajo se aborda la problemática de violencia feminicida cómo la máxima expresión de violencia contra la mujer. Se presentan los antecedentes alrededor de este flagelo en Colombia y cómo ha evolucionado en los años recientes. A partir de ello, se llega a la premisa de que la primera forma de abordar una problemática de esta índole es con una adecuada visibilización. Para lograr una correcta visibilización primero se debe hacer una caracterización y dicha caracterización se nutre de un cuidadoso proceso de extracción de información. De esta manera, en este trabajo final de Maestría se propone un modelo de minería de texto que inicia con la integración de fuentes de información alrededor de la problemática de violencia feminicida en Colombia entre julio de 2017 y diciembre de 2021. Luego, se adecúa la información extraída para identificar señales clave mediante técnicas cómo bolsa de palabras, dendograma, reconocimiento de entidades y clusterización o agrupamiento. A partir de las técnicas previamente mencionadas se realiza una caracterización de los casos de violencia feminicida y se validan los resultados a la luz de la fuente principal de información y datos oficiales de la Fiscalía General de la Nación. Se encuentra que el modelo propuesto ofrece buenos resultados y puede contribuir positivamente al proceso inicial de mitigación de la problemática. Adicionalmente, se plantean algunas fortalezas replicables a otros estudios y algunos aspectos a mejorar en análisis futuros. (tomado de la fuente)In the present work the problem of femicide violence is addressed as the maximum expression of violence against women. It is presented background around this scourge in Colombia and how it has evolved in recent years. From this, is reached the premise that the first way to address a problem of this nature is with adequate visibility. To achieve correct visibility a characterization must be made first and this characterization is nourished by a careful process of information extraction. In this way, in this final Master's project, is proposed a text mining model that begins with the integration of information sources around the problem of femicide violence in Colombia between July 2017 and December 2021. Then, the extracted information is adequated to identify key signals through techniques such as bag of words, dendrogram, entity recognition and clustering or grouping. Based on the previously mentioned techniques, a characterization of the cases of femicide violence is carried out and the results are validated in light of the main source of information and official data of the General Attorney of the Nation. It is found that the proposed model offers good results and can contribute positively to the initial process of mitigating the problem. Additionally, some strengths that can be replicated in other studies and some aspects to improve in future analyzes are proposed.MaestríaMagister en Ingeniería - AnalíticaÁrea Curricular de Ingeniería de Sistemas e Informática81 páginasapplication/pdfspaUniversidad Nacional de ColombiaMedellín - Minas - Maestría en Ingeniería - AnalíticaDepartamento de la Computación y la DecisiónFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín000 - Ciencias de la computación, información y obras generales::003 - SistemasMinería de texto y de datosViolencia contra la mujerViolencia feminicidaMinería de textoViolencia contra la mujerExtracción de informaciónCaracterización de violencia feminicida en ColombiaFemicide violenceText miningViolence against womenInformation extractionCharacterization of femicide violence in ColombiaSeguimiento de casos de feminicidio en Colombia mediante técnicas de minería de textoMonitoring of femicide cases in Colombia using text mining techniquesTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAbbasi, A., & Chen, H. (2007). Affect intensity analysis of dark web forums. ISI 2007: 2007 IEEE Intelligence and Security Informatics, 282–288. https://doi.org/10.1109/isi.2007.379486Allister Simanjuntak, D., & Satriyo Nugroho, A. (2010). Text Classification Techniques used to facilitate Cyber Terrorism Investigation. IEEE Computer Society.Alsaif, H., & Alotaibi, T. (2019). Arabic Text Classification using Feature-Reduction Techniques for Detecting Violence on Social Media.Amrit, C., Paauw, T., Aly, R., & Lavric, M. (2017). Identifying child abuse through text mining and machine learning. Expert Systems with Applications, 88, 402–418. https://doi.org/10.1016/j.eswa.2017.06.035Árevalo Mutiz, P. L. (2018, March 2). Feminicidio en Colombia: avances y retos. https://www.urosario.edu.co/Periodico-NovaEtVetera/Sociedad/Feminicidio-en-Colombia-avances-y-retos/Asik, G. A., & Nas Ozen, E. (2021). It takes a curfew: The effect of Covid-19 on female homicides. Economics Letters, 200, 109761. https://doi.org/10.1016/j.econlet.2021.109761Ayuda en Acción. (2018, July 5). Tipos de violencia contra las mujeres \| Violencia de género. https://ayudaenaccion.org/ong/blog/mujer/tipos-violencia-mujeres/Busso, L., Combei, C. R., & Tordini, O. (2021). Narrating Gender Violence A Corpus-Based Study on the Representation of Gender-Based Violence in Italian Media. Language, Gender and Hate Speech A Multidisciplinary Approach, 39–58. https://doi.org/10.30687/978-88-6969-478-3/002Camelot: PDF Table Extraction for Humans — Camelot 0.10.1 documentation. (n.d.). Retrieved May 12, 2022, from https://camelot-py.readthedocs.io/en/master/Choi, Y. J., Jeon, B. J., & Kim, H. W. (2020). Identification of key cyberbullies: A text mining and social network analysis approach. Telematics and Informatics, June, 101504. https://doi.org/10.1016/j.tele.2020.101504Congreso de la República, C. (2008). Ley 1257 de 2008.Crimen de líder campesino Álvaro Narváez junto a su familia en el Cauca - Otras Ciudades - Colombia - ELTIEMPO.COM. (n.d.). Retrieved May 29, 2022, from https://www.eltiempo.com/colombia/otras-ciudades/crimen-de-lider-campesino-alvaro-narvaez-junto-a-su-familia-en-el-cauca-490528Cronología de las masacres en Colombia durante el año 2020 (Enero a Agosto) DIPAZ. (n.d.). Retrieved May 29, 2022, from https://dipazcolombia.org/masacres-colombia-2020-enero-agosto/E. Perron, B., G. Victor, B., Bushman, G., Moore, A., P. Ryan, J., Jiahong Lu, A., & K. Piellusch, E. (2019). Detecting substance-related problems in narrative investigation summaries of child abuse and neglect using text mining and machine learning. Child Abuse & Neglect.El Ansari, O., Jihad, Z., & Hajar, M. (2020). A dataset to support sexist content detection in arabic text. In Lecture Notes in Computer Science: Vol. 12119 LNCS. Springer International Publishing. https://doi.org/10.1007/978-3-030-51935-3_14El Tiempo. (2020, July 7). CreanSistema de Prevención Temprana de violencias contra las mujeres - Gobierno - Política - ELTIEMPO.COM. https://www.eltiempo.com/politica/gobierno/gobierno-anuncia-sistema-de-prevencion-de-violencia-contra-las-mujeres-515256Fiscalía General de la Nación. (n.d.). Retrieved January 9, 2021, from https://www.fiscalia.gov.co/colombia/Gil, V. D., Betancur, J. D., Puerta, I. C., Montoya, L. M., & Sepulveda, J. M. (2018). the Femicide in Colombia and Mexico: a Text Mining Analysis. The Turkish Online Journal of Design, Art and Communication, 2018(March), 170–177. https://doi.org/10.7456/1080mse/021Greenawald, B., Liu, Y., Wert, G., Al Boni, M., & Brown, D. E. (n.d.). A Comparison of Language-Dependent and Language-Independent Models for Violence Prediction.Gupta, V., & Lehal Professor, G. S. (2009). A Survey of Text Mining Techniques and Applications. www.alerts.yahoo.comHam, E., & Jeong, S. (2021). an Analysis of Korea Newspaper Reporting on Intimate Partner Violence. 58(October 2020), 2692–2700.Hearst, M. (2003). What Is Text Mining?Henshaw, A. (2020). ‘ Peace with a Woman ’ s Face ’: Women , Social Media and the Colombian Peace Process. 42(3), 515–538.Hernández, J., Jiménez, D., Zagal, R., Mata, F., & Borges, J. A. L. (2021). Analysis of the Level of Geographic Criminal Risk Oriented to Women. In Communications in Computer and Information Science: Vol. 1430 CCIS. Springer International Publishing. https://doi.org/10.1007/978-3-030-89586-0_19Home Page - Portal OCM. (n.d.). Retrieved January 9, 2021, from http://www.observatoriomujeres.gov.co/Humberto, F., Murillo, S., Chica, J., Rodríguez, A., & Cortázar, G. De. (2018). The spatial heterogeneity of factors of feminicide : The case of Antioquia- Colombia. Applied Geography, 92(November 2016), 63–73. https://doi.org/10.1016/j.apgeog.2018.01.006Iezzi, D. (2013). Italian Women In The New Millennium: Emancipated Or Violated? An Analysis Of Webmining On Fatal Domestic Violence. Rivista Italiana Di Economia Demografia e Statistica, LXVII(1992). http://www.sieds.it/listing/RePEc/journl/2013LXVII_N2_09_IEZZI.pdfInicio - Instituto Nacional de Medicina Legal y Ciencias Forenses. (n.d.). Retrieved January 9, 2021, from https://www.medicinalegal.gov.co/jaro-winkler · PyPI. (n.d.). Retrieved May 20, 2022, from https://pypi.org/project/jaro-winkler/KADIC, N. (2019). TWITTER RESISTANCE AND DIGITAL TESTIMONIO(S) IN 140 CHARACTERS: RESTORING THE COMPLEXITY OF MEXICO’S HASHTAG FEMINISM. In Copyright by NEIRA KADIC 2019 (Vol. 3). UNIVERSITY OF OKLAHOMA.Karami, A., White, C. N., Ford, K., Swan, S., & Spinel, M. Y. (2020). Unwanted advances in higher education:Uncovering sexual harassment experiences in academia with text mining. Elsevier.Karystianis, G., Adily, A., Schofield, P., Knight, L., Galdon, C., Greenberg, D., Jorm, L., Nenadic, G., & Butler, T. (2019). Automatic Extraction of Mental Health Disorders From Domestic Violence Police Narratives : Text Mining Study. Journal of Medical Internet Research, 20(9), 1–16. https://doi.org/10.2196/11548Karystianis, G., Adily, A., Schofield, P. W., Greenberg, D., Jorm, L., Nenadic, G., & Butler, T. (2019). Automated Analysis of Domestic Violence Police Reports to Explore Abuse Types and Victim Injuries : Text Mining Study. Journal of Medical Internet Research, 21, 1–12. https://doi.org/10.2196/13067Karystianis, G., Simpson, A., Adily, A., Schofield, P., Greenberg, D., Wand, H., Nenadic, G., & Butler, T. (2020). Prevalence of Mental Illnesses in Domestic Violence Police Records : Text Mining Study. Journal of Medical Internet Research, 22. https://doi.org/10.2196/23725Khandokar, I. A., Mamun, I., Chadni, T. I. A., Anas, Z. A., & Shatabda, S. (2020). Event Detection and Knowledge Mining from Unlabelled Bengali News Articles. ETCCE 2020 - International Conference on Emerging Technology in Computing, Communication and Electronics. https://doi.org/10.1109/ETCCE51779.2020.9350891Li, J., & Dong, D. (2019). Keyword Analysis and Topic Extraction of Hospital Violence News. Computer Science & Education.Mohan, V. (n.d.). Preprocessing Techniques for Text Mining-An Overview Privacy Preserving Data Mining View project. Retrieved November 29, 2020, from https://www.researchgate.net/publication/339529230Mouhssine, E., & Khalid, C. (2019). Social Big Data Mining Framework for Extremist Content Detection in Social Networks. International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2018 - Proceedings. https://doi.org/10.1109/ISAECT.2018.8618726Naciones Unidas. (1993). Declaración sobre la Eliminación de la Violencia contra la Mujer.Niklander, S., & Niklander, G. (2017). Combining sentimental and content analysis for recognizing and interpreting human affects. Communications in Computer and Information Science, 713, 465–468. https://doi.org/10.1007/978-3-319-58750-9_64O’halloran, K. L., Tan, S., Wignell, P., Bateman, J. A., Pham, D. S., Grossman, M., & Vande Moere, A. (2016). Interpreting text and image relations in violent extremist discourse: A mixed methods approach for big data analytics. Terrorism and Political Violence, 31(3), 454–474. https://doi.org/10.1080/09546553.2016.1233871Observatorio Feminicidios Colombia. (n.d.). Retrieved January 9, 2021, from https://observatoriofeminicidioscolombia.org/ONU. (n.d.-a). Cómo trabajamos: Eliminación de la violencia contra las mujeres \| ONU Mujeres – Colombia. Retrieved November 14, 2020, from https://colombia.unwomen.org/es/como-trabajamos/violencia-contra-las-mujeresONU. (n.d.-b). Feminicidio \| ONU Mujeres – Colombia. Retrieved October 25, 2020, from https://colombia.unwomen.org/es/como-trabajamos/violencia-contra-las-mujeres/feminicidioONU. (2017). Colombia se unió para decir basta al feminicidio: Ni Una Menos \| ONU Mujeres – Colombia. https://colombia.unwomen.org/es/noticias-y-eventos/articulos/2017/11/exposicionfemÖztürk, N., & Ayvaz, S. (2018). Sentimental analysis on Twitter: A text mining approach to the Syrian refugee crisis. Telematics and Informatics, 136–147.Paulino da Costa, J., Barbosa dos Santos, T. A. M., Carvalho da Mata, E., Silva da Silva, M., & Lisboa Francês, C. R. (2019). DEEP LEARNING : APPLICATION OF THE LSTM MODEL IN THE CATEGORIZATION OF TWEETS ON VIOLENCE IN THE CITY OF BELÉM. ResearchGate, July 2020. https://doi.org/10.33965/bigdaci2019pdfminer.six. (n.d.). Converting a PDF file to text. Retrieved April 23, 2022, from https://pdfminersix.readthedocs.io/en/latest/topic/converting_pdf_to_text.htmlPedraza, G., & María Rodríguez, A. (2016). EL CORTO RECORRIDO DEL FEMINICIDIO EN COLOMBIA. In UNA Revista de Derecho (Vol. 1).Poelmans, J., Elzinga, P., Viaene, S., & Dedene, G. (2011). Formally analysing the concepts of domestic violence. Expert Systems With Applications, 38(4), 3116–3130. https://doi.org/10.1016/j.eswa.2010.08.103Poelmans, J., M. Van Hulle, M., Viaene, S., Elzinga, P., & Dedene, G. (2011). Text mining with emergent self organizing maps and multi-dimensional scaling: A comparative study on domestic violence. Applied Soft Computing.Policía Nacional de Colombia. (n.d.). Retrieved January 9, 2021, from https://www.policia.gov.co/PyPDF2 · PyPI. (n.d.). Retrieved May 12, 2022, from https://pypi.org/project/PyPDF2/Sabbah, T., Selamat, A., Ibrahim, R., & Fujita, H. (2016). Neurocomputing Hybridized term-weighting method for Dark Web classification. 173, 1908–1926. https://doi.org/10.1016/j.neucom.2015.09.063scikit-learn: machine learning in Python — scikit-learn 1.1.1 documentation. (n.d.). Retrieved May 21, 2022, from https://scikit-learn.org/stable/Secretaría Distrital de la Mujer. (n.d.). Tres años de la Ley de Feminicidio. \| Secretaría Distrital de la Mujer. Retrieved October 25, 2020, from http://www.sdmujer.gov.co/noticias/tres-años-la-ley-feminicidioSistema Integrado de Información de Violencias de Género. (n.d.). Retrieved January 9, 2021, from http://onviolenciasgenero.minsalud.gov.co/Paginas/sivige.aspxspaCy · Industrial-strength Natural Language Processing in Python. (n.d.). Retrieved May 21, 2022, from https://spacy.io/Sukanya, M., & Biruntha, S. (2012). Techniques on text mining. Proceedings of 2012 IEEE International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2012, 978, 269–271. https://doi.org/10.1109/ICACCCT.2012.6320784tabula-py · PyPI. (n.d.). Retrieved May 12, 2022, from https://pypi.org/project/tabula-py/Ul Rehman, Z., Abbas, S., Khan, M. A., Mustafa, G., Fayyaz, H., Hanif, M., & Saeed, M. A. (2020). Understanding the language of ISIS: An empirical approach to detect radical content on twitter using machine learning. Computers, Materials and Continua, 66(2), 1075–1090. https://doi.org/10.32604/cmc.2020.012770Vanguardia. (2020, June 27). Ocho medidas del Estado para proteger a las mujeres \| Vanguardia.com. https://www.vanguardia.com/colombia/ocho-medidas-del-estado-para-proteger-a-las-mujeres-YE2547634Varela, N., Gálvez Valega, J. A., & Pineda Lezama, O. B. (2020). Analysis of behavior of automatic learning algorithms to identify criminal messages. Procedia Computer Science, 175, 114–119. https://doi.org/10.1016/j.procs.2020.07.019ViceColombia. (2020, June 26). Gobierno arrecia medidas para frenar violencia contra las mujeres. https://mlr.vicepresidencia.gov.co/Paginas/prensa/2020/Gobierno-arrecia-medidas-para-frenar-violencia-contra-las-mujeres.aspxWang, S. H., Ding, Y., Zhao, W., Huang, Y. H., Perkins, R., Zou, W., & Chen, J. J. (2016). Text mining for identifying topics in the literatures about adolescent substance use and depression. BMC Public Health, 16(1), 4–11. https://doi.org/10.1186/s12889-016-2932-1Watts, C., & Zimmerman, C. (2002). Violence against women: Global scope and magnitude. In Lancet (Vol. 359, Issue 9313, pp. 1232–1237). https://doi.org/10.1016/S0140-6736(02)08221-1Wilson, M., Spike, E., Karystianis, G., & Butler, T. (2021). Nonfatal Strangulation During Domestic Violence Events in New South Wales: Prevalence and Characteristics Using Text Mining Study of Police Narratives. Violence Against Women. https://doi.org/10.1177/10778012211025993wordcloud · PyPI. (n.d.). Retrieved May 21, 2022, from https://pypi.org/project/wordcloud/Xuan Koh, J., & Ming Liew, T. (2020). How loneliness is talked about in social media during COVID-19 pandemic: Text mining of 4,492 Twitter feeds. Journal of Psychiatric Research.Xue, J., Chen, J., & Gelles, R. (2019). Using Data Mining Techniques to Examine Domestic Violence Topics on Twitter. Violence and Gender, 6(2), 105–114. https://doi.org/10.1089/vio.2017.0066Ye In Hwang, J., Zheng, L., Karystiansis, G., Gibbs, V., Sharp, K., & Butler, T. (2020). Domestic violence events involving autism: a text mining study of police records in New South Wales, 2005-2016. Research in Autism Spectrum Disorders.InvestigadoresLICENSElicense.txtlicense.txttext/plain; charset=utf-84675https://repositorio.unal.edu.co/bitstream/unal/82298/1/license.txtb577153cc0e11f0aeb5fc5005dc82d8aMD51ORIGINAL1036955423.2022.pdf1036955423.2022.pdfTesis de Maestría en Ingeniería - Analíticaapplication/pdf1535868https://repositorio.unal.edu.co/bitstream/unal/82298/2/1036955423.2022.pdfb1f8a89d290c3078b5893e4e698e7953MD52THUMBNAIL1036955423.2022.pdf.jpg1036955423.2022.pdf.jpgGenerated Thumbnailimage/jpeg4662https://repositorio.unal.edu.co/bitstream/unal/82298/3/1036955423.2022.pdf.jpgfafafb41a1b743837e0652d6bf988d06MD53unal/82298oai:repositorio.unal.edu.co:unal/822982023-10-06 18:02:42.04Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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

Seguimiento de casos de feminicidio en Colombia mediante técnicas de minería de texto

Publicaciones similares