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T-LAB
Introduction
What T-LAB does and what it enables us to do
Requirements and Performances
Corpus Preparation
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Co-occurrence Analysis
Word Associations
Co-Word Analysis and Concept Mapping
Comparison between Word pairs
Sequence Analysis
Concordances
Thematic Analysis
Thematic Analysis of Elementary Contexts
Modeling of Emerging Themes
Sequences of Themes
Key Contexts of Thematic Words
Thematic Document Classification
Comparative Analysis
Specificity Analysis
Correspondence Analysis
Multiple Correspondence Analysis
Cluster Analysis
Contingency Tables
Lexical Tools
Stop-Word List
Multi-Word List
Corpus Vocabulary
Disambiguation
Dictionary Building
Utilities
Editor
Memo
Variable Manager
Create a Sub-Corpus
Glossary
Analysis Unit
Association Indexes
Chi-Square
Cluster Analysis
Coding
Context Unit
Corpus and Subsets
Correspondence Analysis
Data Table
Disambiguation
Dictionary
Elementary Context
Frequency Threshold
GraphML
Homograph
IDnumber
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Key-Word (Key-Term)
Lemmatization
Lexical Unit
Lexie and Lexicalization
Markov Chain
MDS
Multiwords
Naïve Bayes
Normalization
Occurrences and Co-occurrences
Poles of Factors
Primary Document
Profile
Specificity
Stop Word List
Test Value
Thematic Nucleus
TF-IDF
Variables and Categories
Words and Lemmas
Bibliografia
www.tlab.it

Specificity


In T-LAB, Specificity is the name of a process that allows us to check which lexical units (words, lemmas or categories) are typical or exclusive in a text or a corpus subset defined by some variables.

The "typical" lexical units, defined for over-using or under-using, are detected by means of the chi-square test computation.

The "exclusive" lexical units are those present only within the considered subset and "not" in others.


In this case, the chi-square test requires a repeated crossing among two rows (text and corpus) and two columns (presence and absence of each single word); so that the test has only one degree of freedom and a threshold (5%) equal to the value 3.84.