Abstract
The main objective of this article is to present the Digital Segmentation and Profiling System (SSPD), whose goal is to profile and segment users in social networks based on the analysis of information published by them. To achieve its purpose, SSPD applies natural language processing techniques, graph analysis and machine learning techniques to generate demographic, psychographic, behavioral and sociographic variables that describe the users on the network. To ensure the understanding of the profiles and segments generated, SSPD provides an interactive visualization model that includes a static view and a dynamic view over time. This system is being implemented in Colombia using twitter; however, its flexible architecture makes it possible to apply it to other Spanish-speaking countries and allows its integration with other social networks. © 2017 Sociedad Espanola para el Procesamiento del Lenguaje Natural.
| Translated title of the contribution | Development of a Digital Segmentation and Profiling System |
|---|---|
| Original language | Spanish |
| Article number | 59 |
| Pages (from-to) | 163-166 |
| Number of pages | 5 |
| Journal | Procesamiento de Lenguaje Natural |
| Volume | 59 |
| State | Published - 2017 |