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T-LAB
Introduction
What T-LAB does and what it enables us to do
Requirements and Performances
Corpus Preparation
Corpus Preparation
Structural Criteria
Formal Criteria
File
Import a single file...
Prepare a Corpus (Corpus Builder)
Open an existing project
Settings
Automatic and Customized Settings
Dictionary Building
Co-occurrence Analysis
Word Associations
Co-Word Analysis and Concept Mapping
Comparison between Word pairs
Sequence and Network Analysis
Concordances
Co-occurrence Toolkit
Thematic Analysis
Thematic Analysis of Elementary Contexts
Modeling of Emerging Themes
Thematic Document Classification
Dictionary-Based Classification
Texts and Discourses as Dynamic Systems
Comparative Analysis
Specificity Analysis
Correspondence Analysis
Multiple Correspondence Analysis
Cluster Analysis
Singular Value Decomposition
Lexical Tools
Text Screening / Disambiguations
Corpus Vocabulary
Stop-Word List
Multi-Word List
Word Segmentation
Other Tools
Variable Manager
Advanced Corpus Search
Classification of New Documents
Key Contexts of Thematic Words
Export Custom Tables
Editor
Import-Export Identifiers list
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
Graph Maker
Homograph
IDnumber
Isotopy
Key-Word (Key-Term)
Lemmatization
Lexical Unit
Lexie and Lexicalization
Markov Chain
MDS
Multiwords
N-grams
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
Bibliography
www.tlab.it

Analysis Unit


The analysis units used in T-LAB are of two types: lexical units and context units.

A. - the lexical units are words and multi-words, filed and classified on the basis of a criterion. More precisely, in the T-LAB database each lexical unit consists in a classified record with two fields: word and lemma. In the first field ("word"), the words are listed as they appear in the corpus, while in the second ("lemma") the labels attributed to lexical unit groups are listed and classified according to linguistic criteria (eg. Lemmatization) or by dictionaries and semantic grids defined by the user.


B. - the context units are portions of text that the corpus can be divided into. More precisely, according to T-LAB logic, there can be three types of context units:

B.1 primary documents, which correspond to the "natural" subdivision of the corpus (eg. interviews, articles, answers to open-ended questions, etc.), that is the initial context defined by the user;
B.2 elementary contexts, which correspond to syntagmatic units (i.e. fragments, sentences, paragraphs) in which each primary document can be subdivided;
B.3 corpus subsets, which correspond to groups of primary documents which lead to the same "category" (eg. interviews with "men" or "women", articles in a specific year or a particular magazine and so on).