Many types of texts can be analysed:
speech transcripts, newspaper articles, responses to open-ended
questions, Twitter messages, transcripts of interviews and focus
groups, legislative texts, patents, company documents, books,
More than ten different formats - either documents or
tabular data - are supported: .txt, .doc, .docx, .pdf, .rtf,
.html, .xls, .xlsx, .csv, .mdb, .accdb.
Texts in all languages can be analysed, including those
The whole corpus and its subsets can be analysed by using easily
customizable key-term lists.
is used in about forty countries, and highly valued both by researchers
in leading universities, and professional analysts across many fields.
They include sociologists, marketing
consultants, psychologists, political scientists, economists,
linguists, philosophers, public administration managers, anthropologists,
historians, psychiatrists etc.
The pre-processing steps include: text segmentation,
automatic lemmatisation or stemming, multi-word and stop-word
detection, key-term selection.
Subsequently, three sub-menus allow easy browsing between several
analysis tools allow measuring, exploring and mapping of various
types of relationships between key-terms either in pairs or in
groups, either within the entire corpus or within its subsets
(i.e. newspaper articles from specific time periods, interviews
with people belonging to the same demographic category, etc.).
The thematic analysis tools deal mostly with
finding patterns of key-words within context
units. Actually the way T-LAB allows us to
manage thematic analysis is unique. In fact all analysis units
(i.e. words, text segments and documents) can be grouped either
by a bottom-up or a top-down approach.
The comparative analysis tools enable us
to analyse and map similarities and differences between corpus
subsets, each of which has a specific lexical
profile resulting from the key-terms which occur in it.
Both similarities and differences can be explored either between
pairs or within groups.