Text Analysis in Python for Social Scientists - Discovery and Exploration

A practical guide to text analysis with Python: the intuition, the math, the code.

Table des matières

1. Prerequisites; 2. What's in a Word; 3. Regular Expressions; 4. Pointwise Mutual Information; 5. Representing Text; 6. Matrix Factorization; 7. Clustering; 8. Language Models; 9. Topic Models.

Résumé

Text is a fantastic resource for social scientists, but because it is so abundant, and so variable, it can be difficult to extract the information we want. Many basic text analysis methods are available as Python implementations: this Element will teach you when to use which method, how it works, and the Python code to implement it.

Détails du produit

• Auteurs: Dirk Hovy
• Edition: Cambridge University Press ELT
• Langues: Anglais
• Format d'édition: Livre de poche
• Sortie: 31.12.2020
• EAN: 9781108819824
• ISBN: 978-1-108-81982-4
• Pages: 75
• Thèmes: Elements in Quantitative and C; Elements in Quantitative and Computational Methods for the Social Sciences
• Catégories: Sciences naturelles, médecine, informatique, technique > Informatique, ordinateurs > Informatique; Sciences sociales, droit, économie > Sciences politiques > Sciences politiques et formation politique; Data Mining, SOCIAL SCIENCE / Research, SOCIAL SCIENCE / Statistics, REFERENCE / Research, Social research & statistics, Social research and statistics, COMPUTERS / Data Science / Data Visualization, Research methods: general, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Database Administration & Management, Data capture and analysis, Data Capture & Analysis