Classification of academic events from their textual description

The aim of this paper is to compile dictionaries of slang words, abbreviations, contractions and emoticons to help the preprocessing of texts published in social networks. The use of these dictionaries is intended to improve the results of the tasks related to data obtained from these platforms. The...

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Autores:
Silva, Jesús
Maria Santodomingo, Nicolas Elias
Romero, Ligia
Jorge, Marisol
Herrera, Maritza
Pineda Lezama, Omar Bonerge
Javier Echeverry, Francisco
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
spa
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/7697
Acceso en línea:
https://hdl.handle.net/11323/7697
https://doi.org/10.1007/978-981-15-7234-0_82
https://repositorio.cuc.edu.co/
Palabra clave:
Lexicon
Social networks
Author profiling
Text classification
Rights
openAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 International
id RCUC2_615c21f9aa2e2618e56cbd2595a8871a
oai_identifier_str oai:repositorio.cuc.edu.co:11323/7697
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Classification of academic events from their textual description
title Classification of academic events from their textual description
spellingShingle Classification of academic events from their textual description
Lexicon
Social networks
Author profiling
Text classification
title_short Classification of academic events from their textual description
title_full Classification of academic events from their textual description
title_fullStr Classification of academic events from their textual description
title_full_unstemmed Classification of academic events from their textual description
title_sort Classification of academic events from their textual description
dc.creator.fl_str_mv Silva, Jesús
Maria Santodomingo, Nicolas Elias
Romero, Ligia
Jorge, Marisol
Herrera, Maritza
Pineda Lezama, Omar Bonerge
Javier Echeverry, Francisco
dc.contributor.author.spa.fl_str_mv Silva, Jesús
Maria Santodomingo, Nicolas Elias
Romero, Ligia
Jorge, Marisol
Herrera, Maritza
Pineda Lezama, Omar Bonerge
Javier Echeverry, Francisco
dc.subject.spa.fl_str_mv Lexicon
Social networks
Author profiling
Text classification
topic Lexicon
Social networks
Author profiling
Text classification
description The aim of this paper is to compile dictionaries of slang words, abbreviations, contractions and emoticons to help the preprocessing of texts published in social networks. The use of these dictionaries is intended to improve the results of the tasks related to data obtained from these platforms. Therefore, a hypothesis was evaluated in the task of identifying author profiles (author profiling).
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-01-15T17:47:46Z
dc.date.available.none.fl_str_mv 2021-01-15T17:47:46Z
dc.date.issued.none.fl_str_mv 2021
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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status_str acceptedVersion
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/7697
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.1007/978-981-15-7234-0_82
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
url https://hdl.handle.net/11323/7697
https://doi.org/10.1007/978-981-15-7234-0_82
https://repositorio.cuc.edu.co/
identifier_str_mv Corporación Universidad de la Costa
REDICUC - Repositorio CUC
dc.language.iso.none.fl_str_mv spa
language spa
dc.relation.references.spa.fl_str_mv 1. Schler J, Koppel M, Argamon S, Pennebaker JW (2006) Effects of age and gender on blogging. In: Computational approaches to analyzing weblogs, Papers from the 2006 AAAI spring symposium, Technical Report SS-06-03, Stanford, California, USA, 27–29 March 2006, pp 199–205
2. Viloria A, Lis-Gutiérrez JP, Gaitán-Angulo M, Godoy ARM, Moreno GC, Kamatkar SJ (2018) Methodology for the design of a student pattern recognition tool to facilitate the teaching—learning process through knowledge data discovery (Big Data). In: Tan Y, Shi Y, Tang Q (eds) Data mining and big data. DMBD 2018. Lecture notes in computer science, vol 10943. Springer, Cham
3. Tang J (2016) AMiner: mining deep knowledge from big scholar data. In: Proceedings of the 25th international conference ComEEion on world wide web. International world wide web conferences steering committee, Republic and Canton of Geneva, Switzerland, pp 373–373
4. Obit JH, Ouelhadj D, Landa-Silva D, Vun TK, Alfred R (2011) Designing a multi-agent approach system for distributed course timetabling, pp 103–108. https://doi.org/10.1109/his.2011.6122088
5. Lewis MRR (2006) Metaheuristics for university course timetabling. Ph.D. Thesis, Napier University
6. Deng X, Zhang Y, Kang B, Wu J, Sun X, Deng Y (2011) An application of genetic algorithm for university course timetabling problem, pp 2119–2122. https://doi.org/10.1109/ccdc.2011.5968555
7. Mahiba AA, Durai CAD (2012) Genetic algorithm with search bank strategies for university course timetabling problem. Procedia Eng 38:253–263
8. Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans Knowl Data Eng 17:734–749
9. Camacho-Vázquez V, Sidorov G, Galicia-Haro SN (2016) Machine learning applied to a balanced and emotional corpus of tweets with many varieties of Spanish. Submitted
10. Nguyen K, Lu T, Le T, Tran N (2011) Memetic algorithm for a university course timetabling problem, pp 67–71. https://doi.org/10.1007/978-3-642-25899-2_10
11. Haddi E, Liu X, Shi Y (2013) The role of text pre-processing in sentiment analysis. Procedia Comput Sci 17, 26–32. In: First international conference on information technology and quantitative management
12. Hemalatha I, Varma DGPS, Govardhan DA (2012) Preprocessing the informal text for efficient sentiment analysis. Int J Emerg Trends Technol Comput Sci (IJETTCS) 1(2):58–61
13. Pinto D, Vilariño-Ayala D, Alemán Y, Gómez-Adorno H, Loya N, Jiménez-Salazar H (2012) The soundex phonetic algorithm revisited for sms-based information retrieval. In: II Spanish conference on information retrieval CERI 2012
14. Torres-Samuel M, Vásquez C, Viloria A, Lis-Gutiérrez JP, Borrero TC, Varela N (2018) Web visibility profiles of Top100 Latin American universities. In: International conference on data mining and big data. Springer, Cham, pp 254–262
15. Henao-Rodríguez C, Lis-Gutiérrez JP, Bouza C, Gaitán-Angulo M, Viloria A (2019) Citescore of publications indexed in Scopus: an implementation of panel data. In: International conference on data mining and big data. Springer, Singapore, pp 53–60
16. Peersman C, Daelemans W, Van Vaerenbergh L (2011) Predicting age and gender in online social networks. In: Proceedings of the 3rd international workshop on search and mining user-generated contents. New York, NY, USA, ACM, pp 37–44
17. Nguyen D, Gravel R, Trieschnigg D, Meder T (2013) How old do you think i am?: a study of language and age in twitter. In: Proceedings of the seventh international AAAI conference on weblogs and social media. ICWSM 2013
18. Rangel F, Rosso P (2013) Use of language and author profiling: Identification of gender and age. In: Proceedings of the 10th workshop on natural language processing and cognitive science (NLPCS-2013)
19. Bedford D (2013) Evaluating classification schema and classification decisions. Bull Am Soc Inf Sci Technol 39:13–21
20. Toutanova K, Klein D, Manning C, Singer Y (2003) Feature-rich part-of-speech tagging with a cyclic dependency network. In: Human language technology conference (HLT-NAACL 2003)
21. McGrail MR, Rickard CM, Jones R (2006) Publish or perish: a systematic review of interventions to increase academic publication rates. High Educ Res Dev 25:19–35
22. Costas R, van Leeuwen TN, Bordons M (2010) A bibliometric classificatory approach for the study and assessment of research performance at the individual level: the effects of age on productivity and impact. J Am Soc Inf Sci 61:1564–1581
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dc.source.spa.fl_str_mv Advances in Intelligent Systems and Computing
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spelling Silva, JesúsMaria Santodomingo, Nicolas EliasRomero, LigiaJorge, MarisolHerrera, MaritzaPineda Lezama, Omar BonergeJavier Echeverry, Francisco2021-01-15T17:47:46Z2021-01-15T17:47:46Z2021https://hdl.handle.net/11323/7697https://doi.org/10.1007/978-981-15-7234-0_82Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The aim of this paper is to compile dictionaries of slang words, abbreviations, contractions and emoticons to help the preprocessing of texts published in social networks. The use of these dictionaries is intended to improve the results of the tasks related to data obtained from these platforms. Therefore, a hypothesis was evaluated in the task of identifying author profiles (author profiling).Silva, JesúsMaria Santodomingo, Nicolas EliasRomero, LigiaJorge, MarisolHerrera, MaritzaPineda Lezama, Omar BonergeJavier Echeverry, Franciscoapplication/pdfspaCorporación Universidad de la CostaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Advances in Intelligent Systems and Computinghttps://link.springer.com/chapter/10.1007/978-981-15-7234-0_82LexiconSocial networksAuthor profilingText classificationClassification of academic events from their textual descriptionArtículo 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/acceptedVersion1. Schler J, Koppel M, Argamon S, Pennebaker JW (2006) Effects of age and gender on blogging. In: Computational approaches to analyzing weblogs, Papers from the 2006 AAAI spring symposium, Technical Report SS-06-03, Stanford, California, USA, 27–29 March 2006, pp 199–2052. Viloria A, Lis-Gutiérrez JP, Gaitán-Angulo M, Godoy ARM, Moreno GC, Kamatkar SJ (2018) Methodology for the design of a student pattern recognition tool to facilitate the teaching—learning process through knowledge data discovery (Big Data). In: Tan Y, Shi Y, Tang Q (eds) Data mining and big data. DMBD 2018. Lecture notes in computer science, vol 10943. Springer, Cham3. Tang J (2016) AMiner: mining deep knowledge from big scholar data. In: Proceedings of the 25th international conference ComEEion on world wide web. International world wide web conferences steering committee, Republic and Canton of Geneva, Switzerland, pp 373–3734. Obit JH, Ouelhadj D, Landa-Silva D, Vun TK, Alfred R (2011) Designing a multi-agent approach system for distributed course timetabling, pp 103–108. https://doi.org/10.1109/his.2011.61220885. Lewis MRR (2006) Metaheuristics for university course timetabling. Ph.D. Thesis, Napier University6. Deng X, Zhang Y, Kang B, Wu J, Sun X, Deng Y (2011) An application of genetic algorithm for university course timetabling problem, pp 2119–2122. https://doi.org/10.1109/ccdc.2011.59685557. Mahiba AA, Durai CAD (2012) Genetic algorithm with search bank strategies for university course timetabling problem. Procedia Eng 38:253–2638. Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans Knowl Data Eng 17:734–7499. Camacho-Vázquez V, Sidorov G, Galicia-Haro SN (2016) Machine learning applied to a balanced and emotional corpus of tweets with many varieties of Spanish. Submitted10. Nguyen K, Lu T, Le T, Tran N (2011) Memetic algorithm for a university course timetabling problem, pp 67–71. https://doi.org/10.1007/978-3-642-25899-2_1011. Haddi E, Liu X, Shi Y (2013) The role of text pre-processing in sentiment analysis. Procedia Comput Sci 17, 26–32. In: First international conference on information technology and quantitative management12. Hemalatha I, Varma DGPS, Govardhan DA (2012) Preprocessing the informal text for efficient sentiment analysis. Int J Emerg Trends Technol Comput Sci (IJETTCS) 1(2):58–6113. Pinto D, Vilariño-Ayala D, Alemán Y, Gómez-Adorno H, Loya N, Jiménez-Salazar H (2012) The soundex phonetic algorithm revisited for sms-based information retrieval. In: II Spanish conference on information retrieval CERI 201214. Torres-Samuel M, Vásquez C, Viloria A, Lis-Gutiérrez JP, Borrero TC, Varela N (2018) Web visibility profiles of Top100 Latin American universities. In: International conference on data mining and big data. Springer, Cham, pp 254–26215. Henao-Rodríguez C, Lis-Gutiérrez JP, Bouza C, Gaitán-Angulo M, Viloria A (2019) Citescore of publications indexed in Scopus: an implementation of panel data. In: International conference on data mining and big data. Springer, Singapore, pp 53–6016. Peersman C, Daelemans W, Van Vaerenbergh L (2011) Predicting age and gender in online social networks. In: Proceedings of the 3rd international workshop on search and mining user-generated contents. New York, NY, USA, ACM, pp 37–4417. Nguyen D, Gravel R, Trieschnigg D, Meder T (2013) How old do you think i am?: a study of language and age in twitter. In: Proceedings of the seventh international AAAI conference on weblogs and social media. ICWSM 201318. Rangel F, Rosso P (2013) Use of language and author profiling: Identification of gender and age. In: Proceedings of the 10th workshop on natural language processing and cognitive science (NLPCS-2013)19. Bedford D (2013) Evaluating classification schema and classification decisions. Bull Am Soc Inf Sci Technol 39:13–2120. Toutanova K, Klein D, Manning C, Singer Y (2003) Feature-rich part-of-speech tagging with a cyclic dependency network. In: Human language technology conference (HLT-NAACL 2003)21. McGrail MR, Rickard CM, Jones R (2006) Publish or perish: a systematic review of interventions to increase academic publication rates. High Educ Res Dev 25:19–3522. Costas R, van Leeuwen TN, Bordons M (2010) A bibliometric classificatory approach for the study and assessment of research performance at the individual level: the effects of age on productivity and impact. 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