Big data and automatic detection of topics: social network texts
This paper proposes the analysis of the influence of terms that express feelings in the automatic detection of topics in social networks. This proposal uses an ontology-based methodology which incorporates the ability to identify and eliminate those terms that present a sentimental orientation in so...
- Autores:
-
Silva, Jesús
Hernandez Palma, Hugo Gaspar
Niebles Núñez, William
Ruiz Lázaro, Alex
Varela, Noel
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/6192
- Acceso en línea:
- https://hdl.handle.net/11323/6192
https://repositorio.cuc.edu.co/
- Palabra clave:
- Big Data
Automatic detection
Social network
- Rights
- openAccess
- License
- CC0 1.0 Universal
| Summary: | This paper proposes the analysis of the influence of terms that express feelings in the automatic detection of topics in social networks. This proposal uses an ontology-based methodology which incorporates the ability to identify and eliminate those terms that present a sentimental orientation in social network texts, which can negatively influence the detection of topics. To this end, two resources were used to analyze feelings in order to detect these terms. The proposed system was evaluated with real data sets from the Twitter and Facebook social networks in English and Spanish respectively, demonstrating in both cases the influence of sentimentally oriented terms in the detection of topics in social network texts. |
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