Modeling Students through Analysis of Social Networks Topics
Educational Data Mining gathers the multiple methods that allow new and useful information extraction from great volumes of data coming from the educational context. The goal of this article is to obtain a model of the students of the Computer Science School of the UNLP from their participation in F...
Guardado en:
| Autores principales: | , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2016
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/55814 |
| Aporte de: |
| Sumario: | Educational Data Mining gathers the multiple methods that allow new and useful information extraction from great volumes of data coming from the educational context. The goal of this article is to obtain a model of the students of the Computer Science School of the UNLP from their participation in Facebook. The work describes the process of extraction of latent topics in posts made in public groups related to the School, and the modeling of the students from the topics discovered.
Additionally, it includes the preprocessing done to the collected data, which constitutes a fundamental stage since it strongly conditions the performance of the models to be obtained. Finally, obtained results are presented together with conclusions and future lines of work. |
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