The Argentine economy on Twitter
- Autores
- Aromí, José Daniel; De Raco, Sergio Andrés
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- We propose and implement a methodology for data collection and analysis of Twitter discussions linked to the Argentine economy. Starting with a list of “seed users” later expanded based on following-follower relationships, we build a network of interactions and fetch their tweet timelines. Then, we use a community detection model to compress the structure of underlying relationships and a standard topic model to represent the latent issues discussed in each community. Results suggest that this strategy is able to learn a useful organization and to summarize the contents of social media exchanges of the Argentine economic tweetosphere. Potential applications could be to characterize the links between different economic sectors and to construct community-level indicators of opinions.
Sociedad Argentina de Informática e Investigación Operativa - Materia
-
Ciencias Informáticas
Economics
Social network analysis
Community detection
Topic modeling - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/3.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/140122
Ver los metadatos del registro completo
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The Argentine economy on TwitterAromí, José DanielDe Raco, Sergio AndrésCiencias InformáticasEconomicsSocial network analysisCommunity detectionTopic modelingWe propose and implement a methodology for data collection and analysis of Twitter discussions linked to the Argentine economy. Starting with a list of “seed users” later expanded based on following-follower relationships, we build a network of interactions and fetch their tweet timelines. Then, we use a community detection model to compress the structure of underlying relationships and a standard topic model to represent the latent issues discussed in each community. Results suggest that this strategy is able to learn a useful organization and to summarize the contents of social media exchanges of the Argentine economic tweetosphere. Potential applications could be to characterize the links between different economic sectors and to construct community-level indicators of opinions.Sociedad Argentina de Informática e Investigación Operativa2021-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf15-18http://sedici.unlp.edu.ar/handle/10915/140122enginfo:eu-repo/semantics/altIdentifier/url/http://50jaiio.sadio.org.ar/pdfs/agranda/AGRANDA-03.pdfinfo:eu-repo/semantics/altIdentifier/issn/2683-8966info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/3.0/Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:27:26Zoai:sedici.unlp.edu.ar:10915/140122Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:27:26.43SEDICI (UNLP) - Universidad Nacional de La Platafalse |
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The Argentine economy on Twitter |
| title |
The Argentine economy on Twitter |
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The Argentine economy on Twitter Aromí, José Daniel Ciencias Informáticas Economics Social network analysis Community detection Topic modeling |
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The Argentine economy on Twitter |
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The Argentine economy on Twitter |
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The Argentine economy on Twitter |
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The Argentine economy on Twitter |
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The Argentine economy on Twitter |
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Aromí, José Daniel De Raco, Sergio Andrés |
| author |
Aromí, José Daniel |
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Aromí, José Daniel De Raco, Sergio Andrés |
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author |
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De Raco, Sergio Andrés |
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author |
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Ciencias Informáticas Economics Social network analysis Community detection Topic modeling |
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Ciencias Informáticas Economics Social network analysis Community detection Topic modeling |
| dc.description.none.fl_txt_mv |
We propose and implement a methodology for data collection and analysis of Twitter discussions linked to the Argentine economy. Starting with a list of “seed users” later expanded based on following-follower relationships, we build a network of interactions and fetch their tweet timelines. Then, we use a community detection model to compress the structure of underlying relationships and a standard topic model to represent the latent issues discussed in each community. Results suggest that this strategy is able to learn a useful organization and to summarize the contents of social media exchanges of the Argentine economic tweetosphere. Potential applications could be to characterize the links between different economic sectors and to construct community-level indicators of opinions. Sociedad Argentina de Informática e Investigación Operativa |
| description |
We propose and implement a methodology for data collection and analysis of Twitter discussions linked to the Argentine economy. Starting with a list of “seed users” later expanded based on following-follower relationships, we build a network of interactions and fetch their tweet timelines. Then, we use a community detection model to compress the structure of underlying relationships and a standard topic model to represent the latent issues discussed in each community. Results suggest that this strategy is able to learn a useful organization and to summarize the contents of social media exchanges of the Argentine economic tweetosphere. Potential applications could be to characterize the links between different economic sectors and to construct community-level indicators of opinions. |
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2021 |
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2021-10 |
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