TAToM: Text Analysis with Topic Models for the Humanities and Social Sciences

Keywords: topic model, NLTK, python, chunking, tokenization, MALLET

https://de.dariah.eu/tatom-intro

This tutorial explains basic techniques of text analysis from the very beginning (starting with the introduction of the necessary software and pointing to tutorials on it) and in great detail.

Table of contents:

Preliminaries & Getting started
Working with text
Preprocessing
Feature selection: finding distinctive words
Topic modeling with MALLET
Topic modeling in Python
Visualizing topic models
Classification, Machine Learning, and Logistic Regression
Case Study: Racine’s early and late tragedies

Feedback

Sorry, there is no feedback available. Be the first one to provide feedback!

Resource details

Institution:	DARIAH-DE
Year of publication:	2014
Language:	english
Type:	Tutorial
Audience:
Level:	basic
Prerequisites:	none
Media:	text/html
Objective:
Licence:	CC-BY 4.0
Access:	open
Creation date:	Thursday, 31 July 2014 14:00:04
Last modified:	Thursday, 25 April 2024 00:04:54
BibTeX type:	@misc

BibTeX entry:

@misc(TeLeMaCo:313,
author = "Riddell, Allen",
title = "{T}{A}{T}o{M}: {T}ext {A}nalysis with {T}opic {M}odels for the {H}umanities and {S}ocial {S}ciences",
year = "2014",
url = "https://de.dariah.eu/tatom-intro"
)