Text analysis in Python for social scientists discovery and exploration
Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Man...
| Autor principal: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Cambridge :
Cambridge University Press
2020.
|
| Colección: | CUP ebooks.
Cambridge elements. Elements in quantitative and computational methods for the social sciences. |
| Acceso en línea: | Conectar con la versión electrónica |
| Ver en Universidad de Navarra: | https://innopac.unav.es/record=b44399005*spi |
| Sumario: | Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it. |
|---|---|
| Descripción Física: | 1 recurso electrónico (95 p.) |
| Formato: | Forma de acceso: World Wide Web. |
| ISBN: | 9781108873352 |
