SLAT7829
Preface
Basic Course Information
Course Description
Course Introduction
Course Staff
Timetable
Aims, Objectives & Graduate Attributes
Course Aims
Learning Objectives
Learning Resources
Required Resources
Recommended Resources
University Learning Resources
School of Languages and Cultures Learning Resources
Other Learning Resources & Information
Teaching & Learning Activities
Learning Activities
Course plan
0.1
What is Text Analysis?
0.2
Glossary of Important Concepts
0.3
Text Analysis at UQ
1
Basic Concepts in Text and Corpus Analysis
2
Introduction to AntConc
3
Introduction to AntConc
4
Getting Started with R and RStudio
4.1
Goals of this tutorial
4.2
Audience
4.3
Installing R and RStudio
4.4
Preparation
4.5
Folder Structure and R projects
4.5.1
Create a folder for your project
4.5.2
Open RStudio
4.5.3
R Projects
4.5.4
R Notebooks
4.5.5
Updating R
4.5.6
Optimizing R project options
4.5.7
Getting started with R Notebooks
4.5.8
R Markdown
4.6
R and RStudio Basics
4.7
RStudio: Panes
4.7.1
R Console (bottom left pane)
4.7.2
Running commands from a script
4.7.3
Script Editor (top left pane)
4.8
Getting started with R
4.8.1
Setting up an R session
4.8.2
Packages
4.8.3
Getting help
4.8.4
Finding help within R
4.8.5
Finding help online
5
Working with Tables in R and RStudio
5.1
Working with tables
5.2
Loading data from the web
5.3
Functions and Objects
5.4
Inspecting data
5.5
Accessing individual cells in a table
5.6
Tabulating data
5.7
Saving data to your computer
5.8
Loading data from your computer
5.9
Loading Excel data
5.10
Renaming, Piping, and Filtering
5.11
Ordering data
5.12
Creating and changing variables
5.13
If-statements
5.14
Summarizing data
5.15
Gathering and spreading data
5.16
Ending R sessions
5.17
Extracting session information
5.18
Going further
6
Concordancing with R
6.1
Loading and processing textual data
6.2
Creating simple concordances
6.3
Extracting more than single words
6.4
Searches using regular expressions
6.5
Piping concordances
6.6
Arranging concordances and adding frequency information
6.7
Ordering by subsequent elements
7
Text Analysis and Distant Reading using R
Wordclouds
Frequency changes
Dispersion plots
Over- and underuse
Finding collocations
Visualizing Collocation Networks
Keyness
NER using pacman
NER using NLP and openNLP
8
Analyzing Co-Occurrences and Collocations
Extracting N-Grams with quanteda
Association Strength
Dendrograms
Network Graphs
Basic Network Graphs
Biplots
Simple Collexeme Analysis
Covarying Collexeme Analysis
Distinctive Collexeme Analysis
9
Network Analysis
9.1
What is Network Analysis?
9.2
Preparation and session set up
9.3
Data preparation
9.4
Creating a matrix
9.5
Network Visualization
9.6
Tidy Networks
9.7
Quanteda Networks
9.8
Network Statistics
9.9
What is Part-Of-Speech Tagging?
9.10
POS-Tagging with UDPipe
9.11
POS-Tagging non-English texts
9.12
Dependency Parsing Using UDPipe
10
Sentiment Analysis
Preparation and session set up
Getting started
Binning
Moving average
11
Topic Modeling
Preparation and session set up
Model calculation
Visualization of Words and Topics
Topic distributions
Topic ranking
Approach 1
Approach 2
Filtering documents
Topic proportions over time
Published with bookdown
SLAT7829 Text and Corpus Analysis
Week 3
Introduction to AntConc