Learn about term frequency--inverse document frequency in text analysis in Python with data from how ISIS uses Twitter dataset (2016) /

This dataset is designed for teaching the Term Frequency--Inverse Document Frequency (TFIDF) in text analysis. The dataset is a subset of data derived from the 2016 How ISIS Uses Twitter dataset, and the example demonstrates how TFIDF scores reveal words that are representative of a document and dis...

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Bibliographic Details
Main Author:	Shi, Feng, active 2019 (Author)
Corporate Author:	Odum Institute (Author)
Format:	eBook
Language:	English
Published:	London : SAGE Publications, Ltd., 2019.
Subjects:	Twitter. IS (Organization) Twitter Language and languages > Word frequency. Computational linguistics. Python (Computer program language) Frequency (Linguistics) Fréquence des mots. Linguistique informatique. Python (Langage de programmation) computational linguistics. Computational linguistics Language and languages > Word frequency
Online Access:	Connect to the full text of this electronic book

Description
Summary:	This dataset is designed for teaching the Term Frequency--Inverse Document Frequency (TFIDF) in text analysis. The dataset is a subset of data derived from the 2016 How ISIS Uses Twitter dataset, and the example demonstrates how TFIDF scores reveal words that are representative of a document and distinguish the document from others. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Python.
Physical Description:	1 online resource : illustrations
ISBN:	9781526498038 1526498030