Web platform for the identification and analysis of events on twitter

Due to the great popularity of social networks among people, businesses, public figures, etc., there is a need for automatic methods to facilitate the search, retrieval, and analysis of large amounts of information. Given this situation, the Online Reputation Analyst (ORA) faces the challenge of ide...

Full description

Autores:
amelec, viloria
Varela Izquierdo, Noel
Vargas, Jesús
Pineda, Omar
Tipo de recurso:
http://purl.org/coar/resource_type/c_816b
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/7302
Acceso en línea:
https://hdl.handle.net/11323/7302
https://repositorio.cuc.edu.co/
Palabra clave:
Grouping
Information display
Similarity measurements
Rights
closedAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 International
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repository_id_str
dc.title.spa.fl_str_mv Web platform for the identification and analysis of events on twitter
title Web platform for the identification and analysis of events on twitter
spellingShingle Web platform for the identification and analysis of events on twitter
Grouping
Information display
Similarity measurements
title_short Web platform for the identification and analysis of events on twitter
title_full Web platform for the identification and analysis of events on twitter
title_fullStr Web platform for the identification and analysis of events on twitter
title_full_unstemmed Web platform for the identification and analysis of events on twitter
title_sort Web platform for the identification and analysis of events on twitter
dc.creator.fl_str_mv amelec, viloria
Varela Izquierdo, Noel
Vargas, Jesús
Pineda, Omar
dc.contributor.author.spa.fl_str_mv amelec, viloria
Varela Izquierdo, Noel
Vargas, Jesús
Pineda, Omar
dc.subject.spa.fl_str_mv Grouping
Information display
Similarity measurements
topic Grouping
Information display
Similarity measurements
description Due to the great popularity of social networks among people, businesses, public figures, etc., there is a need for automatic methods to facilitate the search, retrieval, and analysis of large amounts of information. Given this situation, the Online Reputation Analyst (ORA) faces the challenge of identifying relevant issues around an event, product and/or public figure, from which it can propose different strategies to strengthen and/or reverse trends. Therefore, this paper proposes and describes a web tool whose main objective is to support the tasks performed by an ORA. The proposed visualization techniques make it possible to immediately identify the relevance and scope of the opinions generated about an event that took place on Twitter.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-11-13T16:00:41Z
dc.date.available.none.fl_str_mv 2020-11-13T16:00:41Z
dc.date.issued.none.fl_str_mv 2020
dc.date.embargoEnd.none.fl_str_mv 2021-01-31
dc.type.spa.fl_str_mv Pre-Publicación
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REDICUC - Repositorio CUC
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dc.relation.references.spa.fl_str_mv Gonzalez-Agirre A, Laparra E, Laparra G (2012) Multilingual central repository version 3.0. In: Proceedings of the eight international conference on language resources and evaluation (LREC’12). Istanbul, Turkey: European Language Resources Association (ELRA)
Rousseeuw P (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20(1):53–65. [Online]. Disponible: http://ezproxy.cuc.edu.co:2092/10.1016/0377-0427(87)90125-7
Wilcoxon F (1945) Individual comparisons by ranking methods. Bio Bull 1(6):80–83
Toutanova K, Klein D, Manning CD, Singer Y, (2003) Feature-rich part-of-speech tagging with a cyclic dependency network. In: Proceedings of the 2003 conference of the North American chapter of the association for computational linguistics on human language technology, vol 1, ser. NAACL ’03. Stroudsburg, PA, USA: Association for Computational Linguistics, pp 173–180. [Online]. Disponible: http://ezproxy.cuc.edu.co:2092/10.3115/1073445.1073478
Lis-Gutiérrez JP, Gaitán-Angulo M, Henao LC, Viloria A, Aguilera-Hernández D, Portillo-Medina R (2018) Measures of concentration and stability: two pedagogical tools for industrial organization courses. In: Tan Y, Shi Y, Tang Q (eds) Advances in swarm intelligence. ICSI 2018. Lecture Notes in Computer Science, vol 10942. Springer, Cham
Zhao WX, Weng J, He J, Lim E-P, Yan H (2011) Comparing twitter and traditional media using topic models. In: 33rd european conference on advances in information retrieval (ECIR11). Berlin, Heidelberg: Springer-Verlag, pp 338–349
Viloria A, Gaitan-Angulo M (2016) Statistical adjustment module advanced optimizer planner and SAP generated the case of a food production company. Indian J Sci Technol 9(47). https://ezproxy.cuc.edu.co:2067/10.17485/ijst/2016/v9i47/107371
Ansah J, Liu L, Kang W, Liu J, Li J (2020) Leveraging burst in twitter network communities for event detection. World Wide Web, pp 1–26
Sapankevych N, Sankar R (2009) Time series prediction using support vector machines: a survey. IEEE Comput Intell Magaz 4(2):24–38
Viloria A, Lezama OBP (2019) Improvements for determining the number of clusters in k-means for innovation databases in SMEs. Procedia Comput Sci 151:1201–1206
Nugroho R, Paris C, Nepal S, Yang J, Zhao W (2020) A survey of recent methods on deriving topics from Twitter: algorithm to evaluation. Knowl Inf Syst 1–35
Dietrich J, Gattepaille LM, Grum BA, Jiri L, Lerch M, Sartori D, Wisniewski A (2020) Adverse events in twitter-development of a benchmark reference dataset: results from IMI WEB-RADR. Drug Safety 1–12
Romero C, Ventura S (2007) Educational data mining: a survey from 1995 to 2005. Expert Syst Appl 33(1):135–146
Romero C, Ventura S (2010) Educational data mining: a review of the state of the art. Systems, Man, and Cybernet Part C: Appl Rev IEEE Trans 40(6):601–618. Disponible en: http://ezproxy.cuc.edu.co:2063/xpl/RecentIssue.jsp?reload=true&punumber=5326
Choudhury A, Jones J (2014) Crop yield prediction using time series models. J Econom Econom Educat Res 15:53–68
Scheffer T (2004) Finding association rules that trade support optimally against confidence. Intell Data Anal 9(4):381–395
Ruß G (2009) Data mining of agricultural yield data: a comparison of regression models, In: Perner P (eds) Advances in data mining. applications and theoretical aspects, ICDM 2009. Lecture Notes in Computer Science, vol 5633
Amigo E, de Albornoz JC, Chugur I, Corujo A, Gonzalo J, Meij E, de Rijke M, Spina D (2014) Overview of replab 2014: author profiling and reputation dimensions for online reputation management. In: Information access evaluation. Multilinguality, multimodality, and interaction—5th international conference of the CLEF initiative, CLEF 2014, Sheffield, UK, September 15–18, 2014. Proceedings, pp 307–322
Berrocal JLA, Figuerola CG, Rodrıguez AZ (2013) Reina at replab2013 topic detection task: community detection. In: Proceedings of the Fourth International Conference of the CLEF initiative
Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2009) The weka data mining software: an update. SIGKDD Explor Newsl 11(1):10–18
Ramırez-de-la Rosa G, Villatoro-Tello E, Jimenez-Salazar H, Sanchez-Sanchez C (2014) Towards automatic detection of user influence in twitter by means of stylistic and behavioral features. In: Gelbukh A, Espinoza F, Galicia-Haro S (eds) Human-inspired computing and its applications, lecture notes in computer science, vol 8856, pp 245–256. Springer International Publishing
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spelling amelec, viloriaVarela Izquierdo, NoelVargas, JesúsPineda, Omar2020-11-13T16:00:41Z2020-11-13T16:00:41Z20202021-01-3121945357https://hdl.handle.net/11323/7302Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Due to the great popularity of social networks among people, businesses, public figures, etc., there is a need for automatic methods to facilitate the search, retrieval, and analysis of large amounts of information. Given this situation, the Online Reputation Analyst (ORA) faces the challenge of identifying relevant issues around an event, product and/or public figure, from which it can propose different strategies to strengthen and/or reverse trends. Therefore, this paper proposes and describes a web tool whose main objective is to support the tasks performed by an ORA. The proposed visualization techniques make it possible to immediately identify the relevance and scope of the opinions generated about an event that took place on Twitter.amelec, viloria-will be generated-orcid-0000-0003-2673-6350-600Varela Izquierdo, Noel-will be generated-orcid-0000-0001-7036-4414-600Vargas, JesúsPineda, Omar-will be generated-orcid-0000-0002-8239-3906-600application/pdfengCorporación Universidad de la CostaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbAdvances in Intelligent Systems and Computinghttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85090098981&doi=10.1007%2f978-981-15-6876-3_39&partnerID=40&md5=4552c2636bb52e6fd82f3e0c525c0920GroupingInformation displaySimilarity measurementsWeb platform for the identification and analysis of events on twitterPre-Publicaciónhttp://purl.org/coar/resource_type/c_816bTextinfo:eu-repo/semantics/preprinthttp://purl.org/redcol/resource_type/ARTOTRinfo:eu-repo/semantics/acceptedVersionGonzalez-Agirre A, Laparra E, Laparra G (2012) Multilingual central repository version 3.0. In: Proceedings of the eight international conference on language resources and evaluation (LREC’12). Istanbul, Turkey: European Language Resources Association (ELRA)Rousseeuw P (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20(1):53–65. [Online]. Disponible: http://ezproxy.cuc.edu.co:2092/10.1016/0377-0427(87)90125-7Wilcoxon F (1945) Individual comparisons by ranking methods. Bio Bull 1(6):80–83Toutanova K, Klein D, Manning CD, Singer Y, (2003) Feature-rich part-of-speech tagging with a cyclic dependency network. In: Proceedings of the 2003 conference of the North American chapter of the association for computational linguistics on human language technology, vol 1, ser. NAACL ’03. Stroudsburg, PA, USA: Association for Computational Linguistics, pp 173–180. [Online]. Disponible: http://ezproxy.cuc.edu.co:2092/10.3115/1073445.1073478Lis-Gutiérrez JP, Gaitán-Angulo M, Henao LC, Viloria A, Aguilera-Hernández D, Portillo-Medina R (2018) Measures of concentration and stability: two pedagogical tools for industrial organization courses. In: Tan Y, Shi Y, Tang Q (eds) Advances in swarm intelligence. ICSI 2018. Lecture Notes in Computer Science, vol 10942. Springer, ChamZhao WX, Weng J, He J, Lim E-P, Yan H (2011) Comparing twitter and traditional media using topic models. In: 33rd european conference on advances in information retrieval (ECIR11). Berlin, Heidelberg: Springer-Verlag, pp 338–349Viloria A, Gaitan-Angulo M (2016) Statistical adjustment module advanced optimizer planner and SAP generated the case of a food production company. Indian J Sci Technol 9(47). https://ezproxy.cuc.edu.co:2067/10.17485/ijst/2016/v9i47/107371Ansah J, Liu L, Kang W, Liu J, Li J (2020) Leveraging burst in twitter network communities for event detection. World Wide Web, pp 1–26Sapankevych N, Sankar R (2009) Time series prediction using support vector machines: a survey. IEEE Comput Intell Magaz 4(2):24–38Viloria A, Lezama OBP (2019) Improvements for determining the number of clusters in k-means for innovation databases in SMEs. Procedia Comput Sci 151:1201–1206Nugroho R, Paris C, Nepal S, Yang J, Zhao W (2020) A survey of recent methods on deriving topics from Twitter: algorithm to evaluation. Knowl Inf Syst 1–35Dietrich J, Gattepaille LM, Grum BA, Jiri L, Lerch M, Sartori D, Wisniewski A (2020) Adverse events in twitter-development of a benchmark reference dataset: results from IMI WEB-RADR. Drug Safety 1–12Romero C, Ventura S (2007) Educational data mining: a survey from 1995 to 2005. Expert Syst Appl 33(1):135–146Romero C, Ventura S (2010) Educational data mining: a review of the state of the art. Systems, Man, and Cybernet Part C: Appl Rev IEEE Trans 40(6):601–618. Disponible en: http://ezproxy.cuc.edu.co:2063/xpl/RecentIssue.jsp?reload=true&punumber=5326Choudhury A, Jones J (2014) Crop yield prediction using time series models. J Econom Econom Educat Res 15:53–68Scheffer T (2004) Finding association rules that trade support optimally against confidence. Intell Data Anal 9(4):381–395Ruß G (2009) Data mining of agricultural yield data: a comparison of regression models, In: Perner P (eds) Advances in data mining. applications and theoretical aspects, ICDM 2009. Lecture Notes in Computer Science, vol 5633Amigo E, de Albornoz JC, Chugur I, Corujo A, Gonzalo J, Meij E, de Rijke M, Spina D (2014) Overview of replab 2014: author profiling and reputation dimensions for online reputation management. In: Information access evaluation. Multilinguality, multimodality, and interaction—5th international conference of the CLEF initiative, CLEF 2014, Sheffield, UK, September 15–18, 2014. Proceedings, pp 307–322Berrocal JLA, Figuerola CG, Rodrıguez AZ (2013) Reina at replab2013 topic detection task: community detection. In: Proceedings of the Fourth International Conference of the CLEF initiativeHall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2009) The weka data mining software: an update. SIGKDD Explor Newsl 11(1):10–18Ramırez-de-la Rosa G, Villatoro-Tello E, Jimenez-Salazar H, Sanchez-Sanchez C (2014) Towards automatic detection of user influence in twitter by means of stylistic and behavioral features. In: Gelbukh A, Espinoza F, Galicia-Haro S (eds) Human-inspired computing and its applications, lecture notes in computer science, vol 8856, pp 245–256. 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