Determination of the level of user perception through sentiment analysis studies in the context of marketing
Introduction— The comments made by the clients of the companies in the social networks and electronic commerce portals about products and services offered by them, not only allow the companies to determine the perception of the clients for decision making at the marketing level. They serve as a refe...
- Autores:
-
Chanchí Golondrino, Gabriel Elías
Muñoz Sanabria, Luis Freddy
Sierra Martínez, Luz Marina
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2022
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/10018
- Acceso en línea:
- https://hdl.handle.net/11323/10018
https://repositorio.cuc.edu.co/
- Palabra clave:
- Affective computing
Perception level
Opinion mining
Polarity
Sentiment analysis
Computación afectiva
Nivel de percepción
Minería de opinión
Polaridad
Análisis de sentimientos
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
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Determination of the level of user perception through sentiment analysis studies in the context of marketing |
| dc.title.translated.none.fl_str_mv |
Determinación del nivel de percepción de usuario a través de estudios de análisis de sentimientos en el contexto del marketing |
| title |
Determination of the level of user perception through sentiment analysis studies in the context of marketing |
| spellingShingle |
Determination of the level of user perception through sentiment analysis studies in the context of marketing Affective computing Perception level Opinion mining Polarity Sentiment analysis Computación afectiva Nivel de percepción Minería de opinión Polaridad Análisis de sentimientos |
| title_short |
Determination of the level of user perception through sentiment analysis studies in the context of marketing |
| title_full |
Determination of the level of user perception through sentiment analysis studies in the context of marketing |
| title_fullStr |
Determination of the level of user perception through sentiment analysis studies in the context of marketing |
| title_full_unstemmed |
Determination of the level of user perception through sentiment analysis studies in the context of marketing |
| title_sort |
Determination of the level of user perception through sentiment analysis studies in the context of marketing |
| dc.creator.fl_str_mv |
Chanchí Golondrino, Gabriel Elías Muñoz Sanabria, Luis Freddy Sierra Martínez, Luz Marina |
| dc.contributor.author.none.fl_str_mv |
Chanchí Golondrino, Gabriel Elías Muñoz Sanabria, Luis Freddy Sierra Martínez, Luz Marina |
| dc.subject.proposal.eng.fl_str_mv |
Affective computing Perception level Opinion mining Polarity Sentiment analysis |
| topic |
Affective computing Perception level Opinion mining Polarity Sentiment analysis Computación afectiva Nivel de percepción Minería de opinión Polaridad Análisis de sentimientos |
| dc.subject.proposal.spa.fl_str_mv |
Computación afectiva Nivel de percepción Minería de opinión Polaridad Análisis de sentimientos |
| description |
Introduction— The comments made by the clients of the companies in the social networks and electronic commerce portals about products and services offered by them, not only allow the companies to determine the perception of the clients for decision making at the marketing level. They serve as a reference for other customers to make decisions before buying a product. One of the techniques derived from natural language processing and affective computing that allows determining the value of an opinion is sentiment analysis. Objective— To determine a quantitative indicator of the level of perception through a mathematical equation that involves the polarity value (positive, negative, neutral) of an opinion. Methodology— This work focused on the automation of the opinion mining process and the determination of the level of perception through the identification of the most used and suitable libraries for the development of this work; the identification of mathematical equations to determine the level of perception; the implementation of a tool to automate the process; and the verification of its usefulness through a case study. Results— By means of a mathematical equation that involves the three polarities of an opinion, obtaining an automated tool in Python language, which makes use of the Paralleldots library. Conclusions— The tool developed allows opinion mining studies to be carried out in which the added value is the estimation of a level of perception by opinion and in general. The proposed approach is intended to serve as a reference to be replicated and extrapolated in different application contexts in addition to marketing. |
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G. Chanchí Golondrino, L. Muñoz Sanabria & L. Sierra Martínez,“Determination of the level of user perception through sentiment analysis studies in the context of marketing”, INGECUC, vol. 18, no. 2, pp. 238–248. DOI: http://doi.org/10.17981/ ingecuc.18.2.2022.19 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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G. Chanchí Golondrino, L. Muñoz Sanabria & L. Sierra Martínez,“Determination of the level of user perception through sentiment analysis studies in the context of marketing”, INGECUC, vol. 18, no. 2, pp. 238–248. DOI: http://doi.org/10.17981/ ingecuc.18.2.2022.19 0122-6517 10.17981/ ingecuc.18.2.2022.19 2382-4700 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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[1] S. Baldasarri, “Computación Afectiva: tecnología y emociones para mejorar la experiencia de usuario”, Rev Inst Fac Informática, no. 3, pp. 14–15, Jun. 2016. Disponible en http://sedici.unlp.edu.ar/handle/10915/53441 [2] G. Chanchí-Golondrino, C. Hernández-Londoño y M. Ospina-Alarcón, “Aplicación de la computación afectiva en el análisis de la percepción de los asistentes a una feria de emprendimiento del SENA,” Rev Cient, vol. 44, no. 2, pp. 215–227, Ene. 2021. https://doi.org/10.14483/23448350.18971 [3] M. Pouromid, A. Yekkehkhani, M. Oskoei & A. Aminimehr, “ParsBERT Post-Training for Sentiment Analysis of Tweets concerning Stock Market,” presented at 26th International Computer Conference, Computer Society of Iran, CSICC, THR, IR, 3-4 Mar. 2021. https://doi.org/10.1109/ CSICC52343.2021.9420569 [4] H. Lin, T. Wang, G. Lin, S. Cheng, H. Chen & Y. Huang, “Applying sentiment analysis to automatically classify consumer comments concerning marketing 4Cs aspects,” Appl Soft Comput, vol. 97, pp. 1–10, Dec. 2020. https://doi.org/10.1016/J.ASOC.2020.106755 [5] N. Srivats Athindran, S. Manikandaraj & R. Kamaleshwar, “Comparative Analysis of Customer Sentiments on Competing Brands using Hybrid Model Approach,” presented at 3rd International Conference on Inventive Computation Technologies, ICICT, CBE, IN, 15-16 Nov. 2018. https://doi.org/10.1109/ ICICT43934.2018.9034283 [6] F. Khan, U. Qamar & S. Bashir, “eSAP: A decision support framework for enhanced sentiment analysis and polarity classification,” Inf Sci, vol. 367-368, pp. 862–873, Nov. 2016. https://doi.org/10.1016/J. INS.2016.07.028 [7] P. Mukherjee, Y. Badr, S. Doppalapudi, S. Srinivasan, R. Sangwan & R. Sharma, “Effect of Negation in Sentences on Sentiment Analysis and Polarity Detection,” Procedia Comput Sci, vol. 185, pp. 370–379, Jan. 2021. https://doi.org/10.1016/J.PROCS.2021.05.038 [8] A. Moreno-Ortiz & J. Fernández-Cruz, “Identifying Polarity in Financial Texts for Sentiment Analysis: A Corpus-based Approach,” Procedia-Soc Behav Sci, vol. 198, pp. 330–338, Jul. 2015. https://doi. org/10.1016/J.SBSPRO.2015.07.451 [9] G. Chanchí y A. Cordoba, “Análisis de emociones y sentimientos sobre el discurso de firma del acuerdo de paz en Colombia,” RISTI, no. E22, pp. 95–107, Mar. 2019. Available: http://www.risti.xyz/issues/ristie22. pdf [10] G. Chanchí, W. Campo y L. Sierra, “Estudio del atributo satisfacción en pruebas de usabilidad, mediante técnicas de análisis de sentimientos,” RISTI, no. E23, pp. 340–352, May. 2019. Disponible en https://search. proquest.com/openview/dc9c3ac1b6b131619f5c2c7bfa97c1c5/1.pdf?pq-origsite=gscholar&cbl=1006393 [11] V. Gil, “Análisis de sentimientos sobre el impacto social de proyectos de vivienda en América Latina: el caso un TECHO para mi país (Colombia),” Rev. Espac., vol. 39, no. 44, pp. 30-37, May. 2018. Available: http://www.revistaespacios.com/a18v39n44/a18v39n44p30.pdf [12] J. García, P. Henríquez-Coronel, J. Pincai y J. Herrera-Tapia, “Analítica de Twitter para el estudio de las emociones primarias durante el terremoto de México 2017,” RISTI, no. E19, pp. 479–492, Dic. 2018. Disponible en https://www.proquest.com/openview/841aa93ba3c3df451770cecf46615e88/1?pqorigsite=gscholar&cbl=1006393 [13] C. Arcila-Calderón, F. Ortega-Mohedano, J. Jiménez-Amores y S. Trullenque, “Análisis supervisado de sentimientos políticos en español: clasificación en tiempo real de tweets basada en aprendizaje automático,” Prof Inf, vol. 26, no. 5, pp. 973–982, Mar. 2017. https://doi.org/10.3145/epi.2017.sep.18 [14] V. Ikoro, M. Sharmina, K. Malik & R. Batista-Navarro, “Analyzing Sentiments Expressed on Twitter by UK Energy Company Consumers,” presented at 5 International Conference on Social Networks Analysis, Management and Security, ICSNAMS, VAL, ES, 15-18 Oct. 2018. https://doi.org/10.1109/ SNAMS.2018.8554619 [15] S. Ainin, A. Feizollah, N. Anuar & N. Abdullah, “Sentiment analyses of multilingual tweets on halal tourism,” Tour Manag Perspect, vol. 34, pp. 1-8, Jan. 2019. https://doi.org/10.1016/J.TMP.2020.100658 [16] M. Hung, E. Lauren, E. Hon, W. Birmigham, J. Xu, S. Su, S. Hon, J. Park, P. Dang & M. Lipsky, “Social network analysis of COVID-19 sentiments: Application of artificial intelligence,” J Med Internet Res, vol. 22, no. 8, pp. 1–13, Aug. 2020. https://doi.org/10.2196/22590 [17] A. Reyes-Menendez, J. Saura & F. Filipe, “Marketing challenges in the #MeToo era: gaining business insights using an exploratory sentiment analysis,” Heliyon, vol. 6, no. 3, pp. 1–13, Jul. 2019. https://doi. org/10.1016/J.HELIYON.2020.E03626 [18] K. Pratt, Design Patterns for Research Methods: Iterative Field Research, AAAI, May, 2020. Available from http://kpratt.net/wp-content/uploads/2009/01/research_methods.pdf [19] S. Rao, N. Monica, P. Nikhila, T. Tejasri & B. Maram, “Positivity Calculation using Vader Sentiment Analyser”, IJAER, vol. 4, no. 3, pp. 13–17, Mar. 2020. Available from http://ijeais.org/wp-content/ uploads/2020/3/IJAER200303.pdf [20] E. Jacobs, “Mood: Harry Potter,” Erika Jacobs, Jul. 28, 2019. [Online]. Available: https://erika-jacobs. com/post/mood-harry-potter/ |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)Derechos de autor 2022 INGE CUChttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Chanchí Golondrino, Gabriel ElíasMuñoz Sanabria, Luis FreddySierra Martínez, Luz Marina2023-04-25T17:02:32Z2023-04-25T17:02:32Z2022G. Chanchí Golondrino, L. Muñoz Sanabria & L. Sierra Martínez,“Determination of the level of user perception through sentiment analysis studies in the context of marketing”, INGECUC, vol. 18, no. 2, pp. 238–248. DOI: http://doi.org/10.17981/ ingecuc.18.2.2022.190122-6517https://hdl.handle.net/11323/1001810.17981/ ingecuc.18.2.2022.192382-4700Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Introduction— The comments made by the clients of the companies in the social networks and electronic commerce portals about products and services offered by them, not only allow the companies to determine the perception of the clients for decision making at the marketing level. They serve as a reference for other customers to make decisions before buying a product. One of the techniques derived from natural language processing and affective computing that allows determining the value of an opinion is sentiment analysis. Objective— To determine a quantitative indicator of the level of perception through a mathematical equation that involves the polarity value (positive, negative, neutral) of an opinion. Methodology— This work focused on the automation of the opinion mining process and the determination of the level of perception through the identification of the most used and suitable libraries for the development of this work; the identification of mathematical equations to determine the level of perception; the implementation of a tool to automate the process; and the verification of its usefulness through a case study. Results— By means of a mathematical equation that involves the three polarities of an opinion, obtaining an automated tool in Python language, which makes use of the Paralleldots library. Conclusions— The tool developed allows opinion mining studies to be carried out in which the added value is the estimation of a level of perception by opinion and in general. The proposed approach is intended to serve as a reference to be replicated and extrapolated in different application contexts in addition to marketing.Introducción— Los comentarios que realizan los clientes de las empresas en las redes sociales y portales de comercio electrónico sobre productos y servicios ofrecidos por estas, no solo permiten a las empresas determinar la percepción de los clientes para la toma de decisiones a nivel de marketing, sino que también sirven como referencia para otros clientes a tomar decisiones antes de comprar un producto. Una de las técnicas derivadas del procesamiento del lenguaje natural y la computación afectiva que permite determinar el de una opinión es el análisis de sentimiento. Objetivo— Determinar un indicador cuantitativo del nivel de percepción mediante una ecuación matemática que involucra el valor de polaridad (positiva, negativa, neutra) de una opinión. Metodología— Este trabajo se enfocó en la automatización del proceso de minería de opinión y la determinación del nivel de percepción mediante la identificación de las librerías más utilizadas e idóneas para el desarrollo de este trabajo; la identificación de ecuaciones matemáticas para determinar el nivel de percepción, la implementación de una herramienta para automatizar el proceso y la verificación de su utilidad mediante un caso de estudio. Resultados— Por medio de una ecuación matemática que involucra las tres polaridades de una opinión obteniendo una herramienta automatizada en lenguaje Python, que hace uso de la librería Paralleldots. Conclusiones— La herramienta desarrollada permite realizar estudios de minería de opinión en los que el valor agregado es la estimación de un nivel de percepción por opinión y general. El enfoque propuesto pretende servir como referencia para ser replicado y extrapolado en diferentes contextos de aplicación además del marketing.11 páginasapplication/pdfengCorporación Universidad de la CostaColombiahttps://revistascientificas.cuc.edu.co/ingecuc/article/view/4407Determination of the level of user perception through sentiment analysis studies in the context of marketingDeterminación del nivel de percepción de usuario a través de estudios de análisis de sentimientos en el contexto del marketingArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85INGE CUC[1] S. Baldasarri, “Computación Afectiva: tecnología y emociones para mejorar la experiencia de usuario”, Rev Inst Fac Informática, no. 3, pp. 14–15, Jun. 2016. Disponible en http://sedici.unlp.edu.ar/handle/10915/53441[2] G. Chanchí-Golondrino, C. Hernández-Londoño y M. Ospina-Alarcón, “Aplicación de la computación afectiva en el análisis de la percepción de los asistentes a una feria de emprendimiento del SENA,” Rev Cient, vol. 44, no. 2, pp. 215–227, Ene. 2021. https://doi.org/10.14483/23448350.18971[3] M. Pouromid, A. Yekkehkhani, M. Oskoei & A. Aminimehr, “ParsBERT Post-Training for Sentiment Analysis of Tweets concerning Stock Market,” presented at 26th International Computer Conference, Computer Society of Iran, CSICC, THR, IR, 3-4 Mar. 2021. https://doi.org/10.1109/ CSICC52343.2021.9420569[4] H. Lin, T. Wang, G. Lin, S. Cheng, H. Chen & Y. Huang, “Applying sentiment analysis to automatically classify consumer comments concerning marketing 4Cs aspects,” Appl Soft Comput, vol. 97, pp. 1–10, Dec. 2020. https://doi.org/10.1016/J.ASOC.2020.106755[5] N. Srivats Athindran, S. Manikandaraj & R. Kamaleshwar, “Comparative Analysis of Customer Sentiments on Competing Brands using Hybrid Model Approach,” presented at 3rd International Conference on Inventive Computation Technologies, ICICT, CBE, IN, 15-16 Nov. 2018. https://doi.org/10.1109/ ICICT43934.2018.9034283[6] F. Khan, U. Qamar & S. Bashir, “eSAP: A decision support framework for enhanced sentiment analysis and polarity classification,” Inf Sci, vol. 367-368, pp. 862–873, Nov. 2016. https://doi.org/10.1016/J. INS.2016.07.028[7] P. Mukherjee, Y. Badr, S. Doppalapudi, S. Srinivasan, R. Sangwan & R. Sharma, “Effect of Negation in Sentences on Sentiment Analysis and Polarity Detection,” Procedia Comput Sci, vol. 185, pp. 370–379, Jan. 2021. https://doi.org/10.1016/J.PROCS.2021.05.038[8] A. Moreno-Ortiz & J. Fernández-Cruz, “Identifying Polarity in Financial Texts for Sentiment Analysis: A Corpus-based Approach,” Procedia-Soc Behav Sci, vol. 198, pp. 330–338, Jul. 2015. https://doi. org/10.1016/J.SBSPRO.2015.07.451[9] G. Chanchí y A. Cordoba, “Análisis de emociones y sentimientos sobre el discurso de firma del acuerdo de paz en Colombia,” RISTI, no. E22, pp. 95–107, Mar. 2019. Available: http://www.risti.xyz/issues/ristie22. pdf[10] G. Chanchí, W. Campo y L. Sierra, “Estudio del atributo satisfacción en pruebas de usabilidad, mediante técnicas de análisis de sentimientos,” RISTI, no. E23, pp. 340–352, May. 2019. Disponible en https://search. proquest.com/openview/dc9c3ac1b6b131619f5c2c7bfa97c1c5/1.pdf?pq-origsite=gscholar&cbl=1006393[11] V. Gil, “Análisis de sentimientos sobre el impacto social de proyectos de vivienda en América Latina: el caso un TECHO para mi país (Colombia),” Rev. Espac., vol. 39, no. 44, pp. 30-37, May. 2018. Available: http://www.revistaespacios.com/a18v39n44/a18v39n44p30.pdf[12] J. García, P. Henríquez-Coronel, J. Pincai y J. Herrera-Tapia, “Analítica de Twitter para el estudio de las emociones primarias durante el terremoto de México 2017,” RISTI, no. E19, pp. 479–492, Dic. 2018. Disponible en https://www.proquest.com/openview/841aa93ba3c3df451770cecf46615e88/1?pqorigsite=gscholar&cbl=1006393[13] C. Arcila-Calderón, F. Ortega-Mohedano, J. Jiménez-Amores y S. Trullenque, “Análisis supervisado de sentimientos políticos en español: clasificación en tiempo real de tweets basada en aprendizaje automático,” Prof Inf, vol. 26, no. 5, pp. 973–982, Mar. 2017. https://doi.org/10.3145/epi.2017.sep.18[14] V. Ikoro, M. Sharmina, K. Malik & R. Batista-Navarro, “Analyzing Sentiments Expressed on Twitter by UK Energy Company Consumers,” presented at 5 International Conference on Social Networks Analysis, Management and Security, ICSNAMS, VAL, ES, 15-18 Oct. 2018. https://doi.org/10.1109/ SNAMS.2018.8554619[15] S. Ainin, A. Feizollah, N. Anuar & N. Abdullah, “Sentiment analyses of multilingual tweets on halal tourism,” Tour Manag Perspect, vol. 34, pp. 1-8, Jan. 2019. https://doi.org/10.1016/J.TMP.2020.100658[16] M. Hung, E. Lauren, E. Hon, W. Birmigham, J. Xu, S. Su, S. Hon, J. Park, P. Dang & M. Lipsky, “Social network analysis of COVID-19 sentiments: Application of artificial intelligence,” J Med Internet Res, vol. 22, no. 8, pp. 1–13, Aug. 2020. https://doi.org/10.2196/22590[17] A. Reyes-Menendez, J. Saura & F. Filipe, “Marketing challenges in the #MeToo era: gaining business insights using an exploratory sentiment analysis,” Heliyon, vol. 6, no. 3, pp. 1–13, Jul. 2019. https://doi. org/10.1016/J.HELIYON.2020.E03626[18] K. Pratt, Design Patterns for Research Methods: Iterative Field Research, AAAI, May, 2020. Available from http://kpratt.net/wp-content/uploads/2009/01/research_methods.pdf[19] S. Rao, N. Monica, P. Nikhila, T. Tejasri & B. Maram, “Positivity Calculation using Vader Sentiment Analyser”, IJAER, vol. 4, no. 3, pp. 13–17, Mar. 2020. Available from http://ijeais.org/wp-content/ uploads/2020/3/IJAER200303.pdf[20] E. Jacobs, “Mood: Harry Potter,” Erika Jacobs, Jul. 28, 2019. [Online]. Available: https://erika-jacobs. com/post/mood-harry-potter/248238218Affective computingPerception levelOpinion miningPolaritySentiment analysisComputación afectivaNivel de percepciónMinería de opiniónPolaridadAnálisis de sentimientosPublicationORIGINALDetermination of the level of user perception through sentiment analysis studies in the context of marketing.pdfDetermination of the level of user perception through sentiment analysis studies in the context of marketing.pdfArtículoapplication/pdf1467359https://repositorio.cuc.edu.co/bitstreams/71326a0d-1be4-4dbe-a9c4-06e87bca84b4/download35843eb1a0e20f2d2aa978a07854a73aMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://repositorio.cuc.edu.co/bitstreams/32110414-dca1-4342-b0a1-dd96af013b5e/download2f9959eaf5b71fae44bbf9ec84150c7aMD52TEXTDetermination of the level of user perception through sentiment analysis studies in the context of marketing.pdf.txtDetermination of the level of user perception through sentiment analysis studies in the context of marketing.pdf.txtExtracted texttext/plain35798https://repositorio.cuc.edu.co/bitstreams/f96e8d7a-ed9a-41e3-8b29-ad1a707c85e1/download0b97f6276e39672618dedd0e2adaf10dMD53THUMBNAILDetermination of the level of user perception through sentiment analysis studies in the context of marketing.pdf.jpgDetermination of the level of user perception through sentiment analysis studies in the context of marketing.pdf.jpgGenerated Thumbnailimage/jpeg13623https://repositorio.cuc.edu.co/bitstreams/8a47934a-40de-4add-9d62-14591ef68174/download709c04990c87392334a4c8ad7b7f857dMD5411323/10018oai:repositorio.cuc.edu.co:11323/100182024-09-17 11:08:17.343https://creativecommons.org/licenses/by-nc-nd/4.0/Derechos de autor 2022 INGE CUCopen.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa 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ada en las Obras Colectivas.

b.	Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.

c.	Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.
Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).

4. Restricciones.
La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:

a.	Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).

b.	Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.

c.	Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.

d.	Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:

i.	Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.

ii.	Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.

e.	Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.

5. Representaciones, Garantías y Limitaciones de Responsabilidad.
A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

6. Limitación de responsabilidad.
A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

7. Término.

a.	Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.

b.	Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.

8. Varios.

a.	Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.

b.	Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.

c.	Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.

d.	Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.
 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