CONTENTS

List of Tables and Figures

Acknowledgments

1   Introduction

What Is Content Analysis?

Why Use Computerized Analysis Techniques?

Standalone Tools or Integrated Suites

Transitioning from Theory to Practice

Chapter in Summary

2   Obtaining and Preparing Data

Collecting Data from Digital Text Repositories

Are the Data Meaningful?

Using Data in Unintended Ways

Analytical Resolution

Types of Data Sources

Finding Sources

Searching Text Collections

Sources of Incompleteness

Licensing Restrictions and Content Blackouts

Measuring Viewership

Accuracy and Convenience Samples

Random Samples

Multimedia Content

Converting to Textual Format

Prosody

Example Data Sources

Patterns in Historical War Coverage

Competitive Intelligence

Global News Coverage

Downloading Content

Digital Content

Print Content

Preparing Content

Document Extraction

Cleaning

Post Filtering

Reforming/Reshaping

Content Proxy Extraction

Chapter in Summary

3   Vocabulary Analysis

The Basics

Word Histograms

Readability Indexes

Normative Comparison

Non-word Analysis

Colloquialisms: Abbreviations and Slang

Restricting the Analytical Window

Vocabulary Comparison and Evolution/Chronemics

Advanced Topics

Syllables, Rhyming, and “Sounds Like”

Gender and Language

Authorship Attribution

Word Morphology, Stemming, and Lemmatization

Chapter in Summary

4   Correlation and Co-occurrence

Understanding Correlation

Computing Word Correlations

Directionality

Concordance

Co-occurrence and Search

Language Variation and Lexicons

Non-co-occurrence

Correlation with Metadata

Chapter in Summary

5   Lexicons, Entity Extraction, and Geocoding

Lexicons

Lexicons and Categorization

Lexical Correlation

Lexicon Consistency Checks

Thesauri and Vocabulary Expanders

Named Entity Extraction

Lexicons and Processing

Applications

Geocoding, Gazetteers, and Spatial Analysis

Geocoding

Gazetteers and the Geocoding Process

Operating Under Uncertainty

Spatial Analysis

Chapter in Summary

6   Topic Extraction

How Machines Process Text

Unstructured Text

Extracting Meaning from Text

Applications of Topic Extraction

Comparing/Clustering Documents

Automatic Summarization

Automatic Keyword Generation

Multilingual Analysis: Topic Extraction with Multiple Languages

Chapter in Summary

7   Sentiment Analysis

Examining Emotions

Evolution

Evaluation

Analytical Resolution: Documents versus Objects

Hand-crafted versus Automatically Generated Lexicons

Other Sentiment Scales

Limitations

Measuring Language Rather Than Worldview

Chapter in Summary

8   Similarity, Categorization and Clustering

Categorization

The Vector Space Model

Feature Selection

Feature Reduction

Learning Algorithm

Evaluating ATC Results

Benefits of ATC over Human Categorization

Limitations of ATC

Applications of ATC

Clustering

Automated Clustering

Hierarchical Clustering

Partitional Clustering

Document Similarity

Vector Space Model

Contingency Tables

Chapter in Summary

9   Network Analysis

Understanding Network Analysis

Network Content Analysis

Representing Network Data

Constructing the Network

Network Structure

The Triad Census

Network Evolution

Visualization and Clustering

Chapter in Summary

References

Index